{"data":[{"id":11,"title":"Collaborative Statistics","edition_statement":null,"volume":null,"copyright_year":2012,"isbn10":null,"isbn13":"9780978745073","license":"Attribution","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza Collegein Cupertino, California. The textbook was developed over several years and has been used in regularand honors-level classroom settings and in distance learning classes. Courses using this textbook have beenarticulated by the University of California for transfer of credit. The textbook contains full materials forcourse offerings, including expository text, examples, labs, homework, and projects. A Teacher's Guide iscurrently available in print form and on the Connexions site at and supplemental course materials including additional problem sets and video lectures are available. The on-line text for each of these collections collections willmeet the Section 508 standards for accessibility. An on-line course based on the textbook was also developed by Illowsky and Dean. It has won an awardas the best on-line California community college course. The on-line course will be available at a later dateas a collection in Connexions, and each lesson in the on-line course will be linked to the on-line textbookchapter. The on-line course will include, in addition to expository text and examples, videos of courselectures in captioned and non-captioned format. The original preface to the book as written by professors Illowsky and Dean, now follows: This book is intended for introductory statistics courses being taken by students at two– and four–yearcolleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite.The book focuses on applications of statistical knowledge rather than the theory behind it. Thetext is named Collaborative Statistics because students learn best by doing. In fact, they learn best byworking in small groups. The old saying “two heads are better than one” truly applies here. Our emphasis in this text is on four main concepts: thinking statistically incorporating technology working collaboratively writing thoughtfully These concepts are integral to our course. Students learn the best by actively participating, not by justwatching and listening. Teaching should be highly interactive. Students need to be thoroughly engagedin the learning process in order to make sense of statistical concepts. Collaborative Statistics providestechniques for students to write across the curriculum, to collaborate with their peers, to think statistically,and to incorporate technology. This book takes students step by step. The text is interactive. Therefore, students can immediately applywhat they read. Once students have completed the process of problem solving, they can tackle interestingand challenging problems relevant to today's world. The problems require the students to apply theirnewly found skills. In addition, technology (TI-83 graphing calculators are highlighted) is incorporatedthroughout the text and the problems, as well as in the special group activities and projects. The book alsocontains labs that use real data and practices that lead students step by step through the problem solvingprocess. At De Anza, along with hundreds of other colleges across the country, the college audience involves alarge number of ESL students as well as students from many disciplines. The ESL students, as well asthe non-ESL students, have been especially appreciative of this text. They find it extremely readable andunderstandable. Collaborative Statistics has been used in classes that range from 20 to 120 students, and inregular, honor, and distance learning classes.","contributors":[{"id":3699,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Barbara","middle_name":null,"last_name":"Illowsky","location":"De Anza College","background_text":"Barbara Illowsky is a Professor of Mathematics \u0026 Statistics at De Anza College in Cupertino, California. PhD in Education from Capella University."},{"id":3700,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Susan","middle_name":null,"last_name":"Dean","location":"De Anza College","background_text":"Susan Dean is a mathematics professor at De Anza College in Cupertino, California."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"},{"id":82,"name":"Statistics","parent_subject_id":7,"call_number":"QA273-280","visible_textbooks_count":30,"url":"https://open.umn.edu/opentextbooks/%20/subjects/statistics"}],"publishers":[{"id":322,"url":"http://cnx.org/content/col10522/latest/","year":null,"created_at":"2018-09-07T12:22:38.000-05:00","updated_at":"2018-09-07T12:22:38.000-05:00","name":"OpenStax CNX"}],"formats":[{"id":514,"type":"PDF","url":"https://openstax.org/general/cnx-404","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":515,"type":"Hardcopy","url":"https://www.amazon.com/Collaborative-Statistics-Susan-Dean/dp/074421212X","price":{"cents":4200,"currency_iso":"USD"},"isbn":null},{"id":2146,"type":"Online","url":"https://openstax.org/general/cnx-404","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4","textbook_reviews_count":18,"reviews":[{"id":48,"first_name":"Shane","last_name":"Rollans","position":"Senior Lecturer","institution_name":"Thompson Rivers University","comprehensiveness_rating":3,"comprehensiveness_review":"The text covers most of the areas that would normally be included in an introductory course with a few exceptions that I will note later. The index is definitely not effective and I feel that the glossary, while complete, needs revision. Text: The only major topic that is omitted is experimental design but that is not an important omission unless the course is for science or social science students. There is no section on ethics but very few Statistics texts include such a section. Probability plots are not covered and the chapter on regression makes no reference to residual plots which is highly unusual. In my opinion the biggest thing this textbook is missing is motivation for studying statistics. Statistics plays a huge part in trying to answer many important questions and this text gives little or no indication of this. The examples and problems generally deal with uninteresting questions predominantly with made up data. Even when the data is real there is rarely any motivation given or apparent reason to analyze it. Here is an example (pages 398-399) from Chapter 9, Hypothesis Testing: Single Mean and Single Proportion which is typical of most of the student generated questions in the chapter. \"NOTE: The following questions were written by past students. They are excellent problems! Exercise 9.16.18 18. \"Asian Family Reunion\" by Chau Nguyen Every two years it comes around We all get together from different towns. In my honest opinion It's not a typical family reunion Not forty, or fifty, or sixty, But how about seventy companions! The kids would play, scream, and shout One minute they're happy, another they'll pout. The teenagers would look, stare, and compare From how they look to what they wear. The men would chat about their business That they make more, but never less. Money is always their subject And there's always talk of more new projects. The women get tired from all of the chats They head to the kitchen to set out the mats. Some would sit and some would stand Eating and talking with plates in their hands. Then come the games and the songs And suddenly, everyone gets along! With all that laughter, it's sad to say That it always ends in the same old way. They hug and kiss and say \"good-bye\" And then they all begin to cry! I say that 60 percent shed their tears But my mom counted 35 people this year. She said that boys and men will always have their pride, So we won't ever see them cry. I myself don't think she's correct, So could you please try this problem to see if you object?\" I am not sure what hypothesis I am being asked to test here. I would certainly disagree with it being described as an excellent problem. While many of the student generated problems are similar to this one there was one about the endings of Japanese girl's names (9.16.25 Page 402) that I found quite interesting. Index: The index clearly had little or no human input. As well as reasonable entries the index includes a host of random words. For example, the index includes 80 references for the word \"elementary\" and 186 references for the word \"statistics\". It also includes references for many words such as \"answer\", \"box\", \"word\", \"good\" and \"two\" that should not be in any index. Glossary: I would rate the glossary as somewhat effective. The glossary is fairly complete but I believe that many of the entries should be rewritten. It includes some minor errors such as the definition of a geometric distribution \"The probability of exactly x failures before the first success is given by the formula: P (X = x)= p (1- p)^(x-1).\" In at least one case an entry is given with no definition. Some of the other definitions are somewhat unclear. For example: Mutually Exclusive An observation cannot fall into more than one class (category). Being in more than one category prevents being in a mutually exclusive category. Standard Normal Distribution A continuous random variable (RV) X~N (0, 1) .. When X follows the standard normal distribution, it is often noted as Z~N (0, 1). Other definitions just don't match my preferences. For example the definition of correlation includes the so called computational formula which I feel doesn't belong in any statistics textbook. I also didn't like the definition of \"Random Variable\" being given under the heading \"Variable\". Doing that accentuates the confusion between a variable in algebra and a random variable in probability.","accuracy_rating":4,"accuracy_review":"The content is generally accurate and unbiased, although I am not sure what a biased statistics text would look like. There are some errors such as the previously mentioned definition of the geometric distribution which is not much more than a typo and the occasional more serious error such as the statement: \"True random sampling is done with replacement.\" on page 20. In my opinion, virtually every graph in the chapter on graphing is done badly but they are not really errors.","relevance_rating":3,"relevance_review":"This text is a mix, up-to-date in some ways, quite old fashioned in others. It makes good use of graphical calculator technology using the calculator to calculate probabilities rather than using antiquated tables although the tables are still included if an instructor prefers to use them. It also uses the graphical calculator in all aspects of statistical analysis. If you are convinced that a graphical calculator is the best technology to use when teaching introductory statistics, this is one of the primary strengths of the text. The fact that it includes no other technology is a weakness. For example, the text gives long detailed instructions for creating frequency tables and histograms from scratch. I do not feel that this section was done well and even done well it should have disappeared 30 years ago. The text correctly indicates that the normal approximation to the binomial is no longer necessary with the technology that is currently available. However it then uses the same normal approximation when doing inference with proportions. While this is still the norm for introductory classes and should probably be included, it would have been nice to include a justification for using the normal approximation after saying it isn't necessary. One of the first sections I look at when I review a text for possible adoption is the section on comparing means using independent samples. The more modern texts use the Welch's t-test. That is the test used by this text so for me that is a positive. However it follows that section with a long section using the assumption that the variances are known. The variances are never known so the only justification for including such a section is as a lead-in for Welch's t-test. In that case it should be much shorter and should be included first as was done in the single population chapter. While the text indicates \"In practice, we rarely know the population standard deviation.\" (I would replace rarely by never) it devotes more space to the case when the variance or variances are known than when they are unknown. I also check to see if the text differentiates between large and small sample inference for means since there is no reason to do so. This text does not differentiate and it says why which is another plus. As I have mentioned before, this text gives very few examples of what statistics is being used for. Since few of the examples or problems are topical, it will take them a long time to become dated. I would consider this to be a minus but in the context of this question it might be considered a plus. The textbook is written in a way that updates and revisions will be straightforward to implement but in my opinion, so many are needed before I would consider adopting this text that it would not be easy.","clarity_rating":3,"clarity_review":"The text is written very clearly in some places less so in others. It gives a very clear, step by step set of instructions for taking a small simple random sample from an already given sampling frame. However, no mention is made of how difficult it is to create a sampling frame for a large population and no mention is made of how a large simple random sample could be taken from a sampling frame. It also gives relatively clear instructions on how to create a frequency table and histogram including detailed instructions for calculating the number of bars of width 1 required to graph data consisting of the integers 1, 2 ,3 ,4, 5, and 6. (Spoiler: the answer is 6.) It gives a pretty good job of relating decisions using p-values to the concept of rare events. Other parts are less clear. My guess is that no one in a class of tourism students would get anything from the chapter on analysis of variance. It contains lots of jargon with very little context. For example, this is how the description of the F test starts out: \"To calculate the F ratio, two estimates of the variance are made. 1. Variance between samples: An estimate of σ^2 that is the variance of the sample means multiplied by n (when there is equal n). If the samples are different sizes, the variance between samples is weighted to account for the different sample sizes. The variance is also called variation due to treatment or explained variation. 2. Variance within samples: An estimate of σ^2 that is the average of the sample variances (also known as a pooled variance). When the sample sizes are different, the variance within samples is weighted. The variance is also called the variation due to error or unexplained variation.\" While most of the text is written clearly, I feel that a general shortcoming throughout this textbook is that it does not provide sufficient context for the techniques it looks at.","consistency_rating":4,"consistency_review":"The text is consistent in terms of terminology and framework.","modularity_rating":5,"modularity_review":"The text is easily and readily divisible into smaller reading sections; it is not overly self-referential and should be easily reorganized to the extent that any statistics text could be.","organization_rating":4,"organization_review":"The organization is similar to most old-school intro stats texts and while it is not the same as what I use I am sure that it conforms to the organization that many instructors use. The only really awkward place that I noticed was introducing box-plots before measures of centre or location. It meant that the authors had to define quartiles and medians in that section and then define them again later. It would be easy to move the section on box-plots after the discussion of quartiles and medians.","interface_rating":3,"interface_review":"I was working from the pdf file so I cannot comment on these issues.","grammatical_rating":4,"grammatical_review":"I did not notice any grammatical errors.","cultural_rating":4,"cultural_review":"The text is not culturally insensitive or offensive in any way. The names it uses in its examples are inclusive of a variety of ethnicities.","overall_rating":7,"overall_review":"The six recommendations of the GAISE (Guidelines for the Assessment and Instruction in Statistics Education) college report prepared for the American Statistical Association are: 1. Emphasize statistical literacy and develop statistical thinking 2. Use real data 3. Stress conceptual understanding, rather than mere knowledge of procedures 4. Foster active learning in the classroom 5. Use technology for developing conceptual understanding and analyzing data 6. Use assessments to improve and evaluate student learning This textbook does an excellent job on points 4 and 5. There are many group exercises throughout the text. It is a conscious focus of the text and is its primary strength. The textbook is also based on the use of a graphic calculator. While I feel that it is a poor tool for doing statistics, it is a reasonable tool for use in an introductory statistics class. This textbook does an excellent job of integrating it into the curriculum. This is the other strength of the textbook. However, as I mentioned earlier, I feel that ignoring other technologies is a weakness. The book also is less successful in stressing conceptual understanding rather than mere knowledge of procedures, point 3. For example, in the chapter on sampling it gives brief descriptions of different sampling methods but says nothing about the conditions under which one method is better than another. It lists possible problems in sampling but gives no context. Another example is that it lists the properties of correlation but doesn't relate them to data and the only formula given is the computational formula which I feel has no pedagogical value what-so-ever. It uses some real data but I don't feel that it uses enough. The real data it uses does involve the students in the collection of data, making that data more relevant and fostering active learning, obviously a good thing. However, it does not include much data that was used to answer interesting questions. I feel that the critical failure of this textbook is that it doesn't do a good job of teaching statistical thinking. Far too often it emphasizes how to do questions in a textbook rather than how to do statistics. This is a consistent focus throughout the text. Here are a few examples: These listed learning outcomes all talk about textbook questions: \"By the end of this chapter, the student should be able to:\" \"Classify discrete word problems by their distributions.\"(Chapter 4 Page 159) \"Classify continuous word problems by their distributions.\"(Chapter 7 Page 281) \"Discriminate between problems applying the normal and the student-t distributions.\" (Chapter 8 Page 319) As it introduces confidence intervals for proportions it does so in the context of a textbook problem: \"How do you know you are dealing with a proportion problem? First, the underlying distribution is binomial. (There is no mention of a mean or average.)\" (Page 331) In the discussion of using hypothesis testing to make decisions on page 375: \"A systematic way to make a decision of whether to reject or not reject the null hypothesis is to compare the p-value and a preset or preconceived α (also called a \"significance level\"). A preset α is the probability of a Type I error (rejecting the null hypothesis when the null hypothesis is true). It may or may not be given to you at the beginning of the problem.\" When working an example of a test for two means: \"Example 10.1: Independent groups The average amount of time boys and girls ages 7 through 11 spend playing sports each day is believed to be the same. … Is there a difference in the mean amount of time boys and girls ages 7 through 11 play sports each day? Test at the 5% level of significance.\" \"The words \"the same\" tell you Ho has an \"=\". Since there are no other words to indicate Ha, then assume \"is different.\" This is a two-tailed test.\" Another example of the lack of statistical thinking is that while the textbook mentions the assumptions for the various procedures, it never indicates how to assess whether they are reasonable for a particular set of data. The only assumption checking it does is again based on textbook questions rather than data.   For example (Page 381): \"Example 9.13 Statistics students believe that the mean score on the first statistics test is 65. A statistics instructor thinks the mean score is higher than 65. He samples ten statistics students and obtains the scores 65; 65; 70; 67; 66; 63; 63; 68; 72; 71. He performs a hypothesis test using a 5% level of significance. The data are from a normal distribution. … \"Distribution for the test: If you read the problem carefully, you will notice that there is no population standard deviation given. You are only given n = 10 sample data values. Notice also that the data come from a normal distribution. This means that the distribution for the test is a student's-t.\" Since the data are given for the question, the decision on whether to use a t-test should be based on the data, not artificially given in the statement of the question. While this textbook does an excellent job of integrating graphical calculators and includes a large number of collaborative exercises it does not come close to matching my needs for a textbook for an introductory statistics course. I feel that the first three recommendations of the GAISE college report are all critical and I do not believe that this textbook adequately addresses any of the three. I personally would not consider adopting it without extensive revision.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.\r\n ","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":49,"first_name":"Robin","last_name":"Susanto","position":"Instructor","institution_name":"Langara College","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers most of the topics I teach in an Introductory Statistics course, and covers them at the appropriate depth. Two emissions are Experimental Designs and Bayes Theorem. I would like to see more detailed coverage in some areas, such as Sampling and Bias, the Central Limit Theorem for Proportion, and a few others. An explicit explanation on the Scales of Measurement would also be helpful in the discussion on Data and Variable. In Regression I would like to see a discussion on why we should not make prediction outside of the data range. On the other hand, some areas receive more coverage than they should. In the Linear Regression and Correlation, for example, I can do with a lot less manual calculation and sketching of the Least Square line. But overall, coverage and depth is satisfactory. I am able to find what I am looking for in the index. The glossary looks fine.","accuracy_rating":3,"accuracy_review":"The definition of Median (p.59) is incorrect if there are repeated values in the data. Although I understand that, from a pedagogical point of view, it is sometimes preferable to present students, especially at the introductory level, with a 'simplified' definition the can understand intuitively as opposed to a technically correct one that may confuse or discourage learning, a footnote explaining how this definition may not work in some situations is needed. I did not find any other 'errors,' although some definitions, in my opinion, could be better worded.","relevance_rating":3,"relevance_review":"I share the authors' philosophy in making the text contemporary without giving it too short of a shelf life. Most of the examples and exercises are from made-up data. One advantage of this is, unlike real-life data examples, they are not dated, and therefore will not quickly become outdated. Some of the real-life data examples and exercises are student-generated. While this is an excellent way to promote student involvement, I feel that better guidance is needed. For instance, almost all of the student-generated exercises on pp.397-404 were written in verse. Were they instructed to do so? I appreciate originality, and writing Statistics problems in verse is original – unless everyone else is doing it too. Many of these exercises are also lacking from a technical point of view.","clarity_rating":3,"clarity_review":"The language itself is good. It strikes the right balance of accessibility and technical accuracy. This is very important for an Introductory Statistics text, where the main challenge for the instructor is to explain complicated and subtle concepts to students with limited mathematical background, many of whom are ESL students. But some explanations could be better worded. The definitions of type of data and type of variables are confusing. An explicit discussion on scale of measurement is needed.","consistency_rating":4,"consistency_review":"I see no problem with respect to consistency of terminology. The group exercises are also consistent with text's collaborative approach.","modularity_rating":3,"modularity_review":"I usually think of Correlation as an introduction to Regression. And I treat the two as related by separate topics. In the text, they are enmeshed. But other than this, I see no problem with modularity. Although the sequence of topics I use is different from the text. (e.g., I do Correlation and Regression before probability), I don't see any problem with this, as I can easily 'jump around' the text.","organization_rating":4,"organization_review":"I see no problem with the text in this respect.","interface_rating":4,"interface_review":"I see no problem with this item.","grammatical_rating":4,"grammatical_review":"I found a couple of minor typos: p. 18 last paragraph should read: \"Any group of n individuals is equally likely to be chosen as any other group of n individuals.\" p. 532, the second sentence in the first bullet under \"The assumptions underlying the test of significance are:\" should read \"In other words the expected value of y for each particular x value lies on a straight line in the population.\" But these are minor, and I did not notice any other.","cultural_rating":5,"cultural_review":"The examples in the text are inclusive of the cultures that made up the Canadian mosaic. Other than race and ethnicity, it is also important to me that a text is inclusive of people from different economic backgrounds. This text does that. In addition to business examples that refer, for example, to sales figures in the millions of dollars, there are also many examples of situations that working class or middle class people would find themselves in. More examples of small businesses or non-profit would be welcomed.","overall_rating":7,"overall_review":"Most if not all of the examples involving politics are American. It would be nice to see examples involving Canadian political institutions, geography, etc. I think the text does an excellent job in facilitating students' participation and collaboration. Where it falls short is in encouraging Statistical thinking. There is too much rote doing, and recipe-following (e.g. calculation of least-square line), and not enough discussion on why one should choose one statistical procedure over another. This is a serious shortcoming in my opinion. While I consider this text as valuable resource, I will not be adopting it for my class.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":50,"first_name":"RIchard","last_name":"Lockhart","position":"Professor and Chair","institution_name":"Simon Fraser University","comprehensiveness_rating":4,"comprehensiveness_review":"This textbook is very long and covers a certain scope of material very completely at the level it targets. The number of procedures covered starting in Chapter 8 and running to Chapter 13 is very large. However, an instructor, using a textbook like this, would find the comprehensiveness over the top I believe. For instance, probability runs from page 113 to page 251 or so. There is extensive discussion of special distributions: Binomial, Geometric, Hypergeometric, Uniform, Exponential and finally normal. This is much more probability than we would ever do in our courses -- other than our calculus-based course. One of the things I like least about elementary statistics courses is that we continue to teach students to use tables when we never ever use them ourselves. I understand that we find it easiest to give tests where students can use tables but we really need, as a discipline, to move beyond that. There is some focus on computing probabilities using tables but the book does see that tables are no longer really useful or used. Unfortunately the solution adopted here relies on calculators rather than computers. This make it unsuitable for a number of our courses at SFU where computing must be part of the syllabus. For students in the social sciences there are some gaps: the language of scales of measurement (nominal, ordinal, ratio and interval) and the discussion of cross tabulation, contingency tables and measures of association seems to be limited to illustrating probability calculations and then a short section on tests of independence in Chapter 11. My own view is that the explanation of the interpretation of independence is a bit thin. I also notice that quite a number of the contingency table examples have either rows or columns or both which have ordered categories. The usual Pearson chi-squared test is generally a bad idea in this context. I prefer illustrations where the suggested technique is likely to be a good technique.","accuracy_rating":4,"accuracy_review":"I have only a few complaints here. I read phrases I didn't like from time to time but I always feel that way when I read texts. Here are some examples, though, including at least one which bothers me: \"True random sampling is done with replacement.\" Page 20. I would not say this to students -- as if sampling without replacement were some inferior form of survey. \"When you analyze data, it is important to be aware of sampling errors and nonsampling errors. The actual process of sampling causes sampling errors. For example, the sample may not be large enough.\" Page 21. I really don't like joining sample size to the issue of \"sampling errors\". \"For example, in a college population of 10,000 people, suppose you want to randomly pick a sample of 1000 for a survey. For any particular sample of 1000, if you are sampling with replacement, the chance of picking the first person is 1000 out of 10,000 (0.1000); the chance of picking a different second person for this sample is 999 out of 10,000 (0.0999); the chance of picking the same person again is 1 out of 10,000 (very low).\" Page 21. I really don't like this one. What does it mean to say \"the chance of picking the first person is 1000 out of 10,000 (0.1000)\"? This chance seems to distinguish some group of 1000 people from a group of 9000 people. Who are these people? The 1000 people in the sample? What is meant by \"the first person\"? Then why is 999 out of 10,000 the right probability of anything?. It feels like the authors didn't think through what they were saying here very carefully; I hope that does not reflect a general pattern but I confess that I have not read the whole book with the sort of attention needed to spot this sort of problem. \"1.8 Answers and Rounding Off\" on page 26. I think this is fine but do non-science students these days really understand phrases like \"carry your final answer one more decimal place\"? Is the bar graph in example 2.4 a good idea? Indeed is it a good idea to have age groups 13-25 (thirteen years) and then 26-44 (19 years) and 45-64 (20 years)? I don't think so; a histogram here would have quite different bar widths. Even if that is the way the data came from the source we have an obligation to try to help people understand what sort of groups they ought to make. The three dimensional graphs in Example 2.5 probably ought to be discouraged, I think. \"Sampling Distributions and Statistic of a Sampling Distribution\". This is the title of subsection 2.7.2 on page 69. What is \"Statistic of a Sampling Distribution\"? This little subsection contains the phrase \"If you let the number of samples get very large (say, 300 million or more), the relative frequency table becomes a relative frequency distribution.\" If you look at Table 2.6 you are entitle to ask if that contains 1 sample or 30 samples and then ask what it means to \"let the number of samples get very large\"? On page 74 I see mu-bar in the formulas for population standard deviation. \"The statistic of a sampling distribution was discussed in Descriptive Statistics: Measuring the Center of the Data.\" Page 74. Really? I still attach no meaning to the first 6 words of that sentence. Section 3.5 on Contingency Tables. In chapter 3 sample data is often used to DEFINE probabilities. I feel this runs the risk of confusing sample values (the statistics in the tables in this chapter) with population values. Since we spend a lot of effort on this distinction I wonder if it is wise to be so vague about the difference in this context. Do others like the discussion, on pae 159, of \"Random Variable Notation\"? Look at \"If X is a random variable, then X is written in words. and x is given as a number.\" And earlier on the page \"A random variable describes the outcomes of a statistical experiment in words.\" I would find this unteachable but others might cope. In Section 4.5.1 on page 166 I see the phrase \"The parameters are n and p\". I don't see that \"parameter\" has been used in this sense before. I think sometimes the authors are not careful about explaing new words as they use them; they appear to forget occasionally that some of these words have multiple technical uses. In particulart n and p in a Binomial model have not been connected to the population values of some numbers which is the previous meaning assigned to \"parameter\". \"Often real estate prices fit a normal distribution.\" Page 253. Really? I doubt it profoundly. I am not happy about the \"Empirical Rule\". \"About 68.27% of the x values lie between -1s and +1s of the mean m (within 1 standard deviation of the mean).\" That is a lot of digits for an empirical rule and the word \"about\".","relevance_rating":3,"relevance_review":"The text discusses computing only in the context of a specific brand of calculator. When we teach intro stats for social science students, for instance, we introduce them to SPSS -- our client departments (sociology and anthropology, criminology, communications and other arts programs) are very anxious that we do such a thing. The calculator references will be out of date rather quickly and I believe strongly that statistics without computing will leave students with no ability to connect our course with the statistics in their own disciplines. On the other hand the use of calculators is substantially confined to specific sections near the ends of units; perhaps these could be replaced by computing units. I don't think the presentation of the material could be called modern but the basic ideas underlying the Neyman-Pearson approach have not changed so this is probably ok.","clarity_rating":4,"clarity_review":"I think this is true. Occasionally they seem to pick a piece of jargon and re-use it rather than re-explain but generally it is quite all right.","consistency_rating":4,"consistency_review":"I noticed no problems here.","modularity_rating":3,"modularity_review":"I don't think it is all that modular. It feels to me that it might be hard to skip the probability sections and get on to the normal curve directly. That would be a problem for our courses -- we have thirteen weeks to complete the one course most of these students will take and the ideas underlying hypothesis testing and confidence intervals seem to me to be more important that mastering jargon like \"mutually exclusive\".","organization_rating":4,"organization_review":"As Shane Rollans says -- the index is computer generated and not useful. In an on-line / pdf document the page references in an index ought to be active. The actual order is very standard -- that is just fine.","interface_rating":4,"interface_review":"I guess my comment about active links belongs here. I clicked on a number of links in the text and a depressing number did not lead to the objects they should have. This will be a problem for a long time to come in on-line materials and is not limited to this text.","grammatical_rating":4,"grammatical_review":"No complaints from me.","cultural_rating":5,"cultural_review":"No complaints from me.","overall_rating":8,"overall_review":"In the material above I gave some commentary on the specific Review Criteria which we were given.I also want to discuss the issue in terms of who might actually use this text. I am reviewing a textbook for an introductory Statistics course. I have in mind two potential uses of the text: use in some course in my department at SFU; and use in some other post-secondary institution in BC. I am, I think, better qualified to be firm about the value of the text in the former context than in the latter. I will start, then, with the question: is this a useful text for the Statistics and Actuarial Science Department at Simon Fraser University? I think not. Over all I think the text is reasonable and sensible and has no significant technical flaws. But the book is pointed at an audience which is comfortable with more mathematical notation than I think is wise for our non-calculus based courses. At the same time the mathematical level is too low for our calculus based introductions. Thus I doubt that it will be used in any courses we offer. Here are some more details and concerns with respect to actually using the text. We teach three non-calculus introductions (general, social science, and life science students are the three target audiences) and one calculus based introduction. Only in the latter do I use the Greek letters which are used often in this book. I think the formulas and the algebra are not really suitable for the social science non-calculus course and probably would be problematic in our general course as well. Life science students are required to take calculus so the notation may be ok there. In any case I would much prefer a text which did not have so many formulas and symbols for the non-calculus introductions. Look, for instance, at the formula atop page 59 where they solve an equation to find out how many bars are needed in a histogram. I, for one, certainly avoid even the tiniest bit of algebra since it encourages students to think that the algebra is the important part. On collaborative activities: I guess that a lot of instructors would find many of these activities hard to do in a room with 250 students. They might be a good idea, though. I didn't get the feeling that the collaborative activities were terribly central in spite of the title of the book. If I were using this book for a life sciences audience I would be a bit disappointed by the examples, I feel. There are many which use data which is convenient to find on the web or generate in a class or in a small group. I see the value in this but worry that the result is data which is unconnected with the life science material the students are studying elsewhere. I think there is a serious risk that students in a statistics course will fail to see the relevance of the ideas to their own science.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":131,"first_name":"Kurt","last_name":"Colvin","position":"Professor","institution_name":"California Polytechnic State University","comprehensiveness_rating":5,"comprehensiveness_review":"For an introductory course or a reference, this book has comprehensive coverage of the intended content.  Both the table of contents and index are excellent and complete. For my intended use (as a reference book for a senior-level discrete event simulation course), the book covers everything for which I am looking.","accuracy_rating":5,"accuracy_review":"For my several hour review, I could not find a single error or typo. I was not able to determine any bias in presenting the topic (fundamental statistics).","relevance_rating":5,"relevance_review":"The material in this book is the \"bread and butter\" of fundamental statistics. When I look back at my college reference book, the content has not changed. The examples in the book do not indicate a time period. They are simple, generic, easy to understand examples. I do not believe this  book would become obsolete.","clarity_rating":4,"clarity_review":"For the majority of the content, the clarity is excellent. However, at times, I needed to read through the entire section, then revist early paragrpahs to get the entire message. For example, in section 7.1.2 (Introduction to the Central Limit Theorem), the second paragraph discusses \"both alternatives.\" At first, this was very confusing. However, upon finishing the section, then revisiting the paragraph, I did understand the intent. There were several similar examples I found in my review.","consistency_rating":5,"consistency_review":"The format of the chapters is very, very consistent, from the Learning Outcomes, through the exercises, labs and solutions for each chapter. Extremely consistent.","modularity_rating":5,"modularity_review":"Modularity was a strong desire as I searched for a reference book. This book has it in spades. Is it so modular, that one could assign individual sections and, I believe they would  stand independently. For example, one of the sections I will assign is \"Histograms\", section 2.4. That section will stand alone, without having to assign any other material. Excellent modularity.","organization_rating":5,"organization_review":"The topics are presented in increasing complexity. I believe I will use every chapter except, 3, 6, 7 and 12. For my application, I do not need these topics. However, for a fundamental statistics, course, these chapters are necessary, so I am glad they are there. I might have put chapter 13 (ANOVA) right after chapter 10 (Hyp Testing with two means). However, with the excellent modularity, this will not be an issue for me.","interface_rating":4,"interface_review":"I reviewed using the pdf version of the book. This does not have a linked table of contents, which would allow direct access to the sections. I wish the pdf file had this functionality. I am pretty sure this would be available on the online version.","grammatical_rating":5,"grammatical_review":"I could not find any grammatical errors.","cultural_rating":5,"cultural_review":"I do not think this criteria applies for this statistics book. I could not perceive any offensive material in the book.","overall_rating":10,"overall_review":"I was very surprized as the clarity and near-perfect match to my requirements for this statistics reference book. What a find for me and my students. Thank you very much for bringing my attention to Open Textbooks and this statistics reference.","created_at":"2014-07-15T19:00:00.000-05:00","updated_at":"2014-07-15T19:00:00.000-05:00"},{"id":330,"first_name":"Mamfe ","last_name":"Osafo","position":"Mathematics Instructor","institution_name":"Centrral Lakes College ","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers all the areas needed for an Introduction to Statistics or Elementary Statistics. However there should have been instruction on how students can use excel, SPSS, or minitab for some or all the caluculations. ","accuracy_rating":5,"accuracy_review":"I found the contents in the book to be accurate and unbiased. I didn’t find any errors or inaccuracies. ","relevance_rating":4,"relevance_review":"This text has different mix of questions for students to solve which is a good thing for a student taking an Intro to statistics course, but there should have been time period for which the data used in this book was obtained. As mentioned before in my comprehensive comments, it will be good to have a mix of technology use instructions to perform some of the computations, like using Excel, Minitab or SPSS. ","clarity_rating":5,"clarity_review":"The clarity in the book was excellent for an intro to statistics course. The language in the book is clear and concise. I found most instructions in the book to be very detailed and clear for students to follow. The calculator instructions were very clear and easy for a student to follow.","consistency_rating":5,"consistency_review":"The contents in the book is very consistent from beginning to the end. ","modularity_rating":4,"modularity_review":"The text is subdivided well into parts for students to read and understand. Each section can be studied by students. Problems from each sections are independent. I found the text to have no modularity problems. ","organization_rating":5,"organization_review":"This is a well-organized book and flows extremely well but I would recommend the author bringing Chapter 13 F Distribution and ANOVA after Chapter 11 the Chi-Square Distribution. But overall the organization, structure and  flow was well done. ","interface_rating":5,"interface_review":"I don’t find any problem with the interface since I can predict that the text (pdf version) was completely done in latex. I would suggest the author creating a link for the list in the table of contents to the actual pages in the textbook. Hyperlinks for additional resources were created in the pdf formats which makes it easy for students to locate those materials online. There are other options as reading the book online which is a good option for some students. Multiple formats were also available. ","grammatical_rating":5,"grammatical_review":"No grammatical errors were found. ","cultural_rating":4,"cultural_review":"The text was diverse with the examples used in the book and explanations. I do not find any cultural biasness here. ","overall_rating":9,"overall_review":"The text is a good book for an introduction to statistics or elementary statistics. Some improvements can be done on the graphics in the book to make it more attractive and catch the interest of students reading the book. I would recommend more instructors think about reviewing and possibly adopting this book. ","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":385,"first_name":"Kenneth","last_name":"Cheng","position":"Instructor","institution_name":"Portland Community College","comprehensiveness_rating":5,"comprehensiveness_review":"It covers essentially all the topics that would be expected in an introductory statistics course.","accuracy_rating":5,"accuracy_review":"I did not notice any meaningful errors in the book.","relevance_rating":5,"relevance_review":"Statistics at this level of study is considered to be a generally \"complete\" area of study, i.e., one that has not changed significantly in the recent past, nor is expected to in the future.  As such, any statistics book that covers the required topics should not require significant changes.","clarity_rating":3,"clarity_review":"The book is very inconsistent in this regard.  There are times when definitions, contexts, and ideas are made abundantly clear.  Chapter 1, Sampling and Data, is a very good example of that.  \n\nHowever, there are occasions in which this is not true.  A couple of sections leave it to the reader to puzzle out difficult ideas without adequate context, definition, or assistance in defining ideas.  \n\nFor example, the section on hypothesis testing makes it difficult for the student to figure out what they're doing, let alone how to do it.  The discussion weaves from writing null and alternative hypotheses to errors to types of distributions to underlying assumptions to \"rare events\".  As one who understands hypothesis tests, I see where all of these pieces fit in, but I can only imagine that the uninitiated would probably have a difficult time understanding all of these very different pieces of this puzzle.\n\nAs another \n\n","consistency_rating":5,"consistency_review":"With many different topics in statistics, it may not always be best to treat them all the same.  However, notation, vocabulary, and the overall presentation do not vary widely in this booik.","modularity_rating":4,"modularity_review":"Some sections are easier to take apart than others.  This is to be expected.","organization_rating":4,"organization_review":"By and large, the topics (in a big picture sense) are presented in a logical fashion, and prerequisite material is presented before it becomes necessary.","interface_rating":2,"interface_review":"Overall, the interface of the book, as judged by the appearance of the pages, is very plain and monotonous.  It consists of plain black text on plain white pages.  There's essentially no \"prettiness\" within the book.  I have a difficult time imagining that students would find this interesting or something they would want to read, spend time with, and try to understand. \n\nThere are also small details of the typesetting that make this even more difficult.  Often, titles of charts or sections will be \"orphaned\", i.e., the title of a chart will be on one page and the actual chart on the next page.  Many of the graphics have  inconsistent, random, and/or out of place features and/or fonts.  It is difficult to determine the scale of some of the graphs, which could hinder understanding.\n\nAs an example of a place in the text where the writing could make things easier, on page 89, in a summary of formulas, the term \"#ofSTDEVs\" is used as a variable.  It is defined, but the letter z is often used to mean the same thing as a variable  This would be much clearer and more consistent with the uses of that idea later on in the book.  \n\n\n","grammatical_rating":4,"grammatical_review":"The text is completely understandable (to one who has studied statistics) and generally clear.  There are, however, enough minor errors and inconsistencies to warrant notice.  ","cultural_rating":5,"cultural_review":"There is very little cultural reference in this book, which is generally appropriate for a statistics book.  ","overall_rating":8,"overall_review":"It is perfectly adequate as a textbook to guide students through a journey into introductory statistics.  The homework assignments foster understanding, and the labs are an appropriate way to understand the ideas presented in this book.  \n\nWhen I compare it to the more expensive textbook I currently use, the differences are clear.  The text is much plainer, the prose can be inaccessible, the graphics can be inadequate and plain, and the more expensive textbook simply has more of these features to help the instructor and student reach an understanding of statistics.  \n\nWhether the difference in quality is worth the difference in price is a very debatable question. ","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":473,"first_name":"Christopher","last_name":"Stapel","position":"Community Faculty","institution_name":"Metropolitan State University","comprehensiveness_rating":3,"comprehensiveness_review":"This text covers most standard topics in the introductory course in statistics, including sampling, probability, descriptive statistics, and inference. Experimental design receives little attention in the text, but ANOVA is a notable addition. A conceptual understanding of ideas is privileged while computation is deemphasized. Each chapter contains lessons, discussion prompts, collaborative exercises, labs, practice problems, and solutions. Technology tutorials are limited to TI calculators; other statistical packages are not supported. The table of contents provides a nice orientation to the text and the volume is nicely indexed.","accuracy_rating":5,"accuracy_review":"Not only is the content of this text accurate, it is clearly presented and accessible to a wide audience.","relevance_rating":3,"relevance_review":"The content of the text is quite standard and the general topics (notwithstanding some skepticism in some circles about the hegemony of p-values) will likely remain relevant for several years. The topical chapters are modular such that most can be taught in the order of an instructor's choosing and labs, projects, and data are not particularly time-sensitive.\n\nA major limitation of the book is its attachment to TI calculator usage. Given the widespread access to other computational tools--and the relative obsolescence of graphing calculators--the text as written may lack staying power.","clarity_rating":5,"clarity_review":"This is an unequivocal strength of this book. I have taught the introductory course in statistics using several texts and my students have been critical of them all. This text, on the other hand, is readable and targeted to diverse non-majors in a community college setting. I would absolutely feel comfortable assigning reading from this text with the expectation that students come away with an understanding of basic principles.","consistency_rating":4,"consistency_review":"While the book is internally consistent, it could be improved by making more acknowledgements of alternative notations and vocabulary found across disciplines.","modularity_rating":4,"modularity_review":"The chapters are topical and lend themselves to modularity. This is a strength of the text. Given that much of the data is generated by students via collaboration, the modularity may actually pose problems since data is at risk of disappearing if not clearly recorded by students.","organization_rating":5,"organization_review":"I LOVE that solutions to problems are found immediately after the problem sets (rather than at the end of the book). This is a phenomenal innovation! I'm also excited that discussion prompts, collaborative explorations, and labs are integrated through each topical chapter rather than relegated to the end of the chapter. It's as if students have access to the lesson plans and can follow along with classroom prompts and exercises appearing along the way. I no longer have to worry about projecting problems or displaying discussion prompts to accommodate all learners. It's all right in front of them in the text!","interface_rating":3,"interface_review":"I have no major concerns in this respect. The text is not interactive (as some other statistics tests are) so students must manually turn to large data sets and/or to appendices. Bookmarking would be a great addition so that these can be accessed by clicking directly from an exercise.","grammatical_rating":5,"grammatical_review":"The book consistently employs the English language correctly.","cultural_rating":5,"cultural_review":"I certainly found no evidence is insensitivity in the text. In fact the primary audience of the text is a racially diverse community college student body. The problems and activities reflect this diversity and promote a level of cultural competency rivaled by very few, if any, texts.","overall_rating":8,"overall_review":"It's not entirely clear to me what makes this text more collaborative than other instructional materials. While I certainly find the lessons in the book to be active, that does not necessarily imply the titular (collaborative) characteristic. Students collect much of their own data and are charged with working problems in groups or together as a class, but few of the labs and exercises motivate a need for collaboration. Furthermore, students are not given strategies for collaborating statistically and/or mathematically and are not given a satisfactory justification for why collaboration is merited. I don't find this to be a weakness; the active dimensions are a strength of the book, but not wholly collaborative.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":543,"first_name":"Emily","last_name":"Rauscher","position":"Assistant Professor","institution_name":"University of Kansas","comprehensiveness_rating":4,"comprehensiveness_review":"This text covers all of the topics required in most introductory statistics courses – at least social science statistics. Students typically struggle with hypothesis testing. This textbook provides thorough coverage of this topic and many practice questions to allow students to improve their understanding of this topic. In my opinion, it covers probability theory a bit more than necessary for undergraduates, but it is better to err on the side of including rather than excluding.  I do wish, however, that this textbook used R (which is free statistical software) rather than a graphing calculator, which can be expensive and is rarely used in graduate programs.  It is relatively easy, however, to create lab work using R rather than a graphing calculator as used in this textbook.  Overall, this text is substantively comprehensive and includes a useful index and glossary.","accuracy_rating":5,"accuracy_review":"This text is accurate. I may have encountered one small error in the answers provided for a practice problem, but that occurs in expensive statistics textbooks as well and the important points and concepts are accurate, error-free, and unbiased.","relevance_rating":4,"relevance_review":"Introductory statistics is unlikely to change very much in the coming decades. This textbook will not become obsolete anytime in the near future. The specific examples and problems also use current issues and, although the relevance of the issues or specific data used in practice or homework problems may become outdated, it will be very easy to update those things.  In some cases, the questions are not always very applicable to students’ lives.  To make the examples and data in the problems more interesting to students, I often change the text of the problems.  This is very easy to do given the impressive number of questions or problems provided in the textbook.  Graphing calculators seems more likely than the content to become outdated in the near future.  Creating lab work using R rather than a graphing calculator is not difficult.","clarity_rating":5,"clarity_review":"This textbook provides impressively clear explanations of concepts and methods.  I was concerned about this when using this textbook, but was pleased with the clarity of the text for student understanding. The graphics are not as impressive as in expensive textbooks, but this trade-off seems well worth the difference in price.","consistency_rating":5,"consistency_review":"This text uses consistent terminology and framework. For example, each chapter follows a consistent structure and provides practice and homework problems in a similar format.  This consistency makes using this textbook easier for faculty.","modularity_rating":4,"modularity_review":"This textbook is organized in a logical progression through introductory statistics.  However, if instructors chose to teach chapters in a different order, that seems possible.  For example, I believe Chapter 12 Linear Regression and Correlation could be covered earlier than some of the other topics without tremendous confusion on the part of students.  There are certainly some exceptions, however.  For example, Chapter 10 Hypothesis Testing: Two Means, Paired Data, Two Proportions logically follows Chapter 9: Hypothesis Testing: Single Mean and Single Proportion.  Covering these chapters in a different order would likely be more difficult and confuse students.  It is also possible to omit certain topics (e.g., covering less probability theory than the textbook does), with limited problems because the chapters often stand on their own as individual units.","organization_rating":5,"organization_review":"This textbook is well organized and follows a logical and clear progression through the concepts and skills required for introductory statistics.","interface_rating":5,"interface_review":"The text is available as a pdf, which is easy to use and search and students should all be able to access it readily.  Its availability in electronic book format is convenient and students may prefer that version.  The graphics are not as impressive as in expensive textbooks, but this trade-off seems well worth the difference in price.","grammatical_rating":5,"grammatical_review":"The grammar in the textbook is fine and has no noticeable problems.","cultural_rating":4,"cultural_review":"The textbook is not culturally insensitive.  The questions and examples are inclusive of individuals from a variety of backgrounds.  Having said that, the question content is not always highly applicable to students’ lives. However, I am impressed with the number of practice questions and had no problem editing some of the questions to fit students’ lives better and make the material more interesting for them.","overall_rating":9,"overall_review":"Sometimes this textbook loses sight of the bigger picture.  For example, I want students to be able to critically assess statistics they hear in the news or in advertisements.  For example, I think this text could do a better job of emphasizing and illustrating that correlation does not equal causation, or what they should think about when they hear a statistic quoted on television – how did they sample, are there any hidden design issues that raise doubt about that statistic? I am not suggesting these topics are not covered at all (e.g., there is a note on page 534 that correlation does not imply causation), just that instructors may need to emphasize those bigger picture perspectives on their own since the textbook does not always remind students about those things.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":756,"first_name":"Deborah","last_name":"Hendricks","position":"Clinical Associate Professor","institution_name":"West Virginia University","comprehensiveness_rating":5,"comprehensiveness_review":"The text is very comprehensive of the materials I teach in a first semester statistics course. I sometimes include Two-Way ANOVA, but not always depending on how well student progress through the preceding materials. This would not, however, impact my decision to use this text.","accuracy_rating":5,"accuracy_review":"I found the book to be very accurate. The formulas were well presented. Definitions of terms were accurate and easily understood even by those with limited mathematical background.","relevance_rating":5,"relevance_review":"The content is current and the examples involve common items, events, and situations to almost everyone's lives. This should give the text a very high level of longevity and the relevance is fantastic across a wide range of academic programs.","clarity_rating":5,"clarity_review":"The clarity is exceptional. The definitions, descriptions, formulas, examples, and problems all were presented in very accessible terms and were easy to understand. The material was presented using very creative approaches that made it interesting and (dare I say) entertaining to read.","consistency_rating":5,"consistency_review":"The text is consistent. The material was presented in a logical flow that built appropriately from one topic to the next. ","modularity_rating":5,"modularity_review":"The layout and organization are consistent with many other statistics texts. The chapters are logical and well ordered. The index makes it particularly easy to locate specific terms, tests, practice problems, and homework assignments.","organization_rating":5,"organization_review":"Very appropriate and logical organization. Information is presented from the simple to the more complex types of analyses. Each chapter builds on the material presented in earlier chapters in an appropriate order.","interface_rating":5,"interface_review":"Everything appeared to be clear, appropriately sized, etc. No real issues noted related to the interface. There were some diagrams that seemed a bit over-sized, but that certainly is not a problem.","grammatical_rating":5,"grammatical_review":"The only thing I noted was in the very first paragraph where a sentence ended with ?\".   That period outside the end quote should not be present. Other than that, I did not note any other grammatical or punctuation problems. And the readability was outstanding for a statistics text.","cultural_rating":5,"cultural_review":"No problems noted in this area. The text appropriately refers to a number of minority cultures.","overall_rating":10,"overall_review":"LOVE this text! The definitions and formulas are all explained in clear terms. The examples are interesting and clearly illustrate the intended concept. The formulas are presented in both words and symbols, which is wonderful for students who do not have a strong mathematical background. The problems are interesting. I loved the Hamlet exercise that represented many statistical concepts. Extremely creative educational methods on the part of these authors. This text definitely busts the myth that statistical texts have to be dull, boring tomes that are better suited to ending insomnia. This one is interesting and vibrant, while still providing good, solid instruction. I'm sure my students would love this book and I would love to teach from it. Well done!","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":1584,"first_name":"David","last_name":"Grollimund","position":"Assistant Professor","institution_name":"Colorado State University - Pueblo","comprehensiveness_rating":4,"comprehensiveness_review":"\nThe text includes topics one would expect to find in an introductory statistics course for non-math majors.  The index, while functional, is not extremely polished.  As other reviewers have mentioned, some less than useful words are indexed or important words are overly indexed so that it can be difficult to find the actual discussion concerning that term in the text.\n\nI was disappointed to find a lack of discussion on the use of residual plots in chapter 12.","accuracy_rating":5,"accuracy_review":"Formulas and definitions seem to be free from error.  Examples included in the chapters have accurate solutions.","relevance_rating":4,"relevance_review":"According to the linked website at cnx.org, the latest update was about 3 years ago.  While the text remains accurate and relevant, a small number of the URL links in the pdf textbook do not work or link to documents that seem to be placeholders.\nThe authors do include instructions for the use of technology at appropriate points in the chapters.  However, these instructions are limited only to the use of specific calculators, the TI 83 and 84 series.  These sections could be arranged in such a way that updates can include instructions for TI Nspire and other calculators or even software like R.\n\n","clarity_rating":4,"clarity_review":"The authors do a great job of maintaining a conversational tone with the reader.  Considering the intended audience is majors outside of mathematics and engineering, this tone allows the reader to remain comfortable with the topic.  I do think there are times when more intuitive discussions could follow the presentation of a formula or definition.  The text can sometimes focus more on telling the reader how to do something with little attention as to why one may want to do so, why it's useful, or a brief rationale for why it works.","consistency_rating":5,"consistency_review":"The layout of each chapter is consistent.  The reader quickly becomes familiar with how each chapter is presented and knows what to expect.  Terminology is also consistent.","modularity_rating":5,"modularity_review":"This text should not present any difficulties in regards to reorganization of certain topics.  Obviously, there will be some requirements when it comes to sequencing that are part of the nature of the course, but the content is presented in sections that are divided at natural breaking points resulting in self-contained areas that provide the instructor with a decent level of modularity.","organization_rating":5,"organization_review":"In my sampling of the text, I did find some areas that presented some issues with organization or flow.  Occasionally a term is used before it is defined.  This may present an issue for some students.  For example, in section 1.2.2, the authors discuss the four levels of measurement and state that the nominal scale is qualitative.  The term qualitative is not defined until later in section 1.5.  On a larger scale, though, the chapters are organized logically and in a manner consistent with other similar texts.","interface_rating":4,"interface_review":"Charts and graphs appear to be clear and easy to read.  I did have some readability issues with the PDF in regards to page breaks.  Occasionally, a new heading/subheading, exercise, or example would start with a single or few lines of text at the bottom of a page before continuing with significantly more text on the next page.  I found that I had to flip back and forth between pages on my computer or tablet when this occurred if using an electronic version of the text.  This was a minor inconvenience.","grammatical_rating":5,"grammatical_review":"I found no obvious grammatical errors in my sampling of the text.","cultural_rating":4,"cultural_review":"I did not find any cases where the text was culturally insensitive.  Efforts towards inclusion mainly occur through the use of examples or exercises that reference different ethnicities or backgrounds.","overall_rating":9,"overall_review":null,"created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":1664,"first_name":"Deborah","last_name":"Wall","position":"Asst. Professor","institution_name":"American University","comprehensiveness_rating":5,"comprehensiveness_review":"Book covers the topics we currently cover in our Basic Statistics course","accuracy_rating":5,"accuracy_review":"The book is accurate and the sample of pages I reviewed were well-written and unbiased.","relevance_rating":5,"relevance_review":"The book does not appear to be tied to any particular technology.  The instructor will need to supplement with instructions on using the technology of choice.","clarity_rating":5,"clarity_review":"Well-written and easy to understand.","consistency_rating":5,"consistency_review":"Terminology and framework is consistent.","modularity_rating":5,"modularity_review":"It is broken into many small pieces and includes several sections that are clearly identified as optional.","organization_rating":5,"organization_review":"Clear organization.  Covers confidence intervals for several types of problems and then addresses hypothesis testing.","interface_rating":5,"interface_review":"I had difficulty accessing the videos, but would love to see them.  Some exercises are presented with an option to see the solution.","grammatical_rating":5,"grammatical_review":"Grammar is error-free.  ","cultural_rating":5,"cultural_review":"I did not notice anything offensive.","overall_rating":10,"overall_review":"very well-written text.  I would like to consider adopting this as our text.","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":1674,"first_name":"Larry","last_name":"Musolino","position":"Lecturer, Mathematics","institution_name":"Penn State University","comprehensiveness_rating":4,"comprehensiveness_review":"The textbook is very comprehensive and appears to cover most topics in an introductory statistics course.  One topic that does not appear to be addressed is Two Way Anova Testing.   Another topic that is not covered is hypothesis testing for standard deviations.","accuracy_rating":5,"accuracy_review":"The textbook appears to be very accurate.  I did not observe any numerical errors or other obvious errors.","relevance_rating":4,"relevance_review":"The book is very relevant and will apply since statistical concepts will generally not need to be updated.  Many of the examples are universal in nature and will still remain relevant for some time to come.   There are a few examples that apply to current cultural trends which may become outdated but there are not too many of these examples so this should not be an issue.","clarity_rating":5,"clarity_review":"The textbook is very clear and laid out in a logical manner.  The examples are clear and show step by step worked out solutions.  Any notation or symbols are defined and explained in easy to understand language such that students will not be confused by notation which is a common problem in statistics.","consistency_rating":5,"consistency_review":"The book is very consistent and is clearly defined in terms of the notation and symbol used in the book.\nThe same notation and terminology is used for example in confidence intervals and in hypothesis testing.","modularity_rating":3,"modularity_review":"The text is nicely laid out and organized and can be modularized depending on an instructors preference.\nVarious chapters can be omitted or covered in an order dictated by the instructor.  For example correlation and regression is covered in a manner wherein an instructor can cover this earlier in the sequence of topics.\n","organization_rating":5,"organization_review":"The organization and flow is logical and the statistical concepts are presented in a clear and logical order.   The concepts start with simpler statistical concepts and then advance to more involved concepts such as confidence intervals, hypothesis testing, ANOVA","interface_rating":5,"interface_review":"The interface is based on PDF format which is convenient for students and allows them to download the text to a laptop, tablet, etc.","grammatical_rating":5,"grammatical_review":"I did not observe any grammatical errors.","cultural_rating":4,"cultural_review":"The cultural relevance is fine and there are many student based examples which will likely be relevant and understandable to students. ","overall_rating":9,"overall_review":"Overall, I feel the text does a good job of covering various topics from an introductory statistics course.","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":1785,"first_name":"Angela","last_name":"Fishman","position":"Assistant Teaching Professor","institution_name":"Penn State University","comprehensiveness_rating":5,"comprehensiveness_review":"The contents are very typical of any introductory statistics book and more than enough for a 3-credit course for non-majors.","accuracy_rating":5,"accuracy_review":"I found no obvious errors in the sections I read and problems I attempted.  I may find one or two when I use this in my course next semester.","relevance_rating":5,"relevance_review":"I find the examples timeless and student relevant.  I will probably supplement with data from current events anyway.","clarity_rating":5,"clarity_review":"It is written at a student level.  I find the  verbage to be very student friendly.","consistency_rating":5,"consistency_review":"Seems adequate.  The probabllity chapter is somewhat \"mathy\" but it is hard not to be.","modularity_rating":5,"modularity_review":"The sections are short enough to not lose a student in the reading of any one concept.","organization_rating":5,"organization_review":"his is organized in a sequential manner just as any basic statistics book needs to be.","interface_rating":5,"interface_review":"The graphics are basic enough that students will be able to replicate them in Excel given hands-on assignments.","grammatical_rating":5,"grammatical_review":"Seems adequate.","cultural_rating":4,"cultural_review":"I usually gauge the content for each individual class of students.  There are always opportunities to add discussions from current news events.","overall_rating":10,"overall_review":"After reviewing this one and the one more standard one by the same authors, i am tempted to utilize this version.  The additional videos are enticing for the student who needs/wants more.","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":1805,"first_name":"Whitney","last_name":"Zimmerman","position":"Assistant Teaching Professor","institution_name":"The Pennsylvania State University","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers the topics typically covered in a traditional undergraduate-level introductory statistics course. I did notice that the text does not cover effect size and statistical power is only briefly covered. These are two concepts that I believe deserve more attention. The text does not teach any statistical software.","accuracy_rating":5,"accuracy_review":"Textbook is accurate.","relevance_rating":3,"relevance_review":"The field of statistics education is moving toward the use of simulations and hands-on activities. An instructor can supplement this text with such activities, but these activities are not include in this text. This text covers a traditional curriculum which may be replaced by simulation-based inference methods in the future. ","clarity_rating":3,"clarity_review":"The text appears to be very formula heavy. As stated earlier, some concepts such as effect size and statistical power are not given enough attention. Students with strong mathematics backgrounds may be more comfortable with this text than students with weaker mathematics backgrounds. ","consistency_rating":5,"consistency_review":"Chapters have a consistent look. ","modularity_rating":4,"modularity_review":"The chapters are well organized. There are optional sections for topics that are not taught in all introductory courses. I would suggest some formatting be used to distinguish between formulas, worked examples, practice problems, etc. Most of the text is in black and white.","organization_rating":5,"organization_review":"Chapters are logically ordered. Topics are presented in an order that is consistent with most similar introductory texts.","interface_rating":4,"interface_review":"Graphs look like they may have been made in Excel which may be a positive or negative depending on the instructor or department's attitudes towards the use of Excel as a statistical software. \nAs stated earlier, some formatting to distinguish between formulas, examples, and homework questions would be preferred. ","grammatical_rating":5,"grammatical_review":"No noted grammatical issues. ","cultural_rating":5,"cultural_review":"Text occasionally refers to male/female as gender (as opposed to sex). No other noted issues. ","overall_rating":9,"overall_review":"Currently I teach introductory statistics 100% online. I would not use use this text because it does not meet my needs (e.g., no statistical software, too formula driven for my students, no simulations). \n\nGiven it's cost, I may consider using it in a small face-to-face course where I could teach statistical software and simulations and just use the text as an additional resource and practice problems. ","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":2559,"first_name":"Jenna","last_name":"Kowalski","position":"Mathematics Instructor","institution_name":"Minnesota State","comprehensiveness_rating":5,"comprehensiveness_review":"The text includes the introductory statistics topics covered in a college-level semester course.  An effective index and glossary are included, with functional hyperlinks.  Embedded solutions for each exercise are thorough, and lectures videos and instructor’s teaching manual are well-defined.  ","accuracy_rating":5,"accuracy_review":"The content of this text is accurate and error-free, based on a random sampling of various pages throughout the text.  Several examples included information with formal citation, which is a best-teaching practice. ","relevance_rating":5,"relevance_review":"The text contains relevant information that is current and will not become outdated in the near future.  The statistical formulas and calculations have been used for centuries.  The examples are direct applications of the formulas and accurately assess the conceptual knowledge of the reader.  ","clarity_rating":5,"clarity_review":"The text is very clear and direct with the language used.  The jargon does require a basic mathematical and/or statistical foundation to interpret, but this foundational requirement should be met with course prerequisites and placement testing.  Graphs, tables, and visual displays are clearly labeled.  ","consistency_rating":5,"consistency_review":"The terminology and framework of the text is consistent.  The hyperlinks are working effectively, and the glossary is valuable.  Each chapter contains subsections that begin with prerequisite information and upcoming learning objectives for mastery.  ","modularity_rating":5,"modularity_review":"The sections are clearly defined and can be used in conjunction with other sections, or individually to exemplify a choice topic.  With the prerequisite information stated, the reader understands what prior mathematical understanding is required to successfully use the particular section.  ","organization_rating":5,"organization_review":"The topics are presented well, and consistent with current Introductory Statistics texts.  The structure is very organized with the prerequisite information stated and upcoming learner outcomes highlighted.  Each section is well-defined. ","interface_rating":4,"interface_review":"Adding an option of returning to the previous page would be of great value to the reader.  While progressing through the text systematically, this is not an issue, but when the reader chooses to skip section content and read select pages then returning to the previous state of information is not easily accessible.  ","grammatical_rating":5,"grammatical_review":"No grammatical errors were found while reviewing select pages of this text at random.  ","cultural_rating":5,"cultural_review":"This text incorporates inclusive teaching practices and no apparent bias was observed. The variety of examples was well-informed and addressed different identifiers in an equitable manner.  ","overall_rating":10,"overall_review":"The embedded solutions manual for the exercises is incredibly valuable to educators who choose to use this text.  The associated teacher’s manual is thorough and comprehensive.  ","created_at":"2019-02-06T15:34:18.000-06:00","updated_at":"2019-02-06T15:34:18.000-06:00"},{"id":2593,"first_name":"Sharon","last_name":"Emerson-Stonnell","position":"Professor","institution_name":"Longwood University","comprehensiveness_rating":4,"comprehensiveness_review":"The textbook has an easily accessible index and glossary.  However, there are areas that might need to be supplemented.  If you want to build intuition about the normal distribution using the 68-95-99.7 rule, you will need to add this material.  Also, the textbook does not include proportions in the Central Limit Theorem chapter. This may need to be supplemented before the Confidence Interval chapter, which includes proportions.","accuracy_rating":5,"accuracy_review":"The textbook is mathematically accurate and the authors have chosen unbiased, accessible examples.","relevance_rating":5,"relevance_review":"The text covers material covered in traditional freshmen statistics courses.   This textbook assumes TI-83 usage.  The TI-84 is still closely related.  However, if students use Casio, there will need to be supplements added. ","clarity_rating":5,"clarity_review":"The authors try to use correct statistical terms but also try to explain them using accessible examples.  There are practice exercises in each section that can be used for classroom or group discussions.","consistency_rating":5,"consistency_review":"Each chapter uses the same format and students can easily find exercises at the end of each chapter.  Each new definition or process is followed by examples that are worked through step-by-step.  Calculator usage is also carefully explained. ","modularity_rating":5,"modularity_review":"Each chapter is divided into smaller sections.  Each smaller section contains a practice exercise that can be used for class or group practice.","organization_rating":5,"organization_review":"Each chapter is divided into sections of new material followed by labs that can be assigned in or out of class as group activities then exercises.  The exercises are nicely divided into beginning problems that walk students through the process, then multiple choice problems, and finally problems that students must work through on their own.  There are also review problems that help students practice previous material.","interface_rating":4,"interface_review":"While the flow of each chapter is nice, the students must scroll through each section to get to the next section.  It would be nice to be able to click and go directly to the exercises or labs.","grammatical_rating":5,"grammatical_review":"The authors relate the material well to the students' level.","cultural_rating":4,"cultural_review":"The authors have included data collection that is appropriate for all students.  Their inclusion of humanities such as the literature analysis in the proportion section of hypothesis testing is admirable.  However, in their desire to include multiple majors, natural science examples might need to be supplemented.","overall_rating":9,"overall_review":"This is a nice textbook for an introductory freshman statistics course, especially if you use TI calculators in class and on tests.","created_at":"2019-03-01T09:34:06.000-06:00","updated_at":"2019-03-01T09:34:06.000-06:00"},{"id":2697,"first_name":"Noureddine","last_name":"Benchama","position":"Unlimited Math faculty","institution_name":"Minnesota State","comprehensiveness_rating":5,"comprehensiveness_review":"I recommend enriching the book by a section on MISLEADING statistics.\r\nThe book is rich with additional material actually. I would recommend having the Binomial, Normal and t-distribution tables instead of a link that may become inexistent.","accuracy_rating":4,"accuracy_review":"The book could cover statistical life more fairly by adding data and examples about state economies and infrastructures, international business and organizations, etc.\r\nIn hypothesis testing, it is stated that \"the null hypothesis is false, therefore the alternate hypothesis in true\". We know this to be a false deduction: a false Ho only means it needs to be rejected and a new Ho formulated, then tested. Statistical tests decide on the null hypothesis, they never validate or invalidate an alternate hypothesis.","relevance_rating":5,"relevance_review":"Only the technology use part may need updating as computing evolves quickly.","clarity_rating":4,"clarity_review":"Some concepts need more clarification, like the types of sampling methods in chapter 1. Also, in introducing topics, sometimes it is better to do so inductively instead of providing a definition first.","consistency_rating":5,"consistency_review":"The organization of chapter is maintained all through the text. I noticed no inconsistencies.","modularity_rating":5,"modularity_review":"The books succeeds here but I suggest cutting some non required parts and providing them as links optionally: Stat Labs and Collaborative Exercises are not going to be used by faculty who may prefer their own activities.","organization_rating":5,"organization_review":"I suggest putting all the \"Try It\" exercises at the end of the section.","interface_rating":4,"interface_review":"The quality of graphs can be improved: they seems fuzzy and not proportional to the space needed. The tables need size adjustment as well.","grammatical_rating":5,"grammatical_review":"No significantly occurring grammatical problem.","cultural_rating":4,"cultural_review":"The book could be enriched with more data on minorities, college statistics (cost, career, job rates, etc.), economic and health data of under performing and successful countries on such indicators as education, health, environment. \r\n","overall_rating":9,"overall_review":"I suggest including the basic use of R language, a small manual on using Excel.\r\nI also suggest providing more historical background to the development of inferential statistics.","created_at":"2019-03-25T19:10:10.000-05:00","updated_at":"2019-03-25T19:10:10.000-05:00"},{"id":4727,"first_name":"Jennifer","last_name":"Koran","position":"Associate Professor","institution_name":"Southern Illinois University Carbondale","comprehensiveness_rating":5,"comprehensiveness_review":"The index and glossary in this text are impressive in their level of detail.  The chapters cover all topics that are typically included in an introductory undergraduate applied statistics course.","accuracy_rating":5,"accuracy_review":"I found no errors or bias in the content.  I was very glad to see that when teaching hypothesis testing, the authors use reject or do not reject the null hypothesis, rather than reject or accept the null hypothesis.  The former dichotomy more accurately relays the meaning of the decision about the null hypothesis.  I also thought it was particularly accurate that the authors introduced the normal distribution by emphasizing that it is common and important but cannot be applied to everything in the real world.","relevance_rating":4,"relevance_review":"Relevance is always a challenge with statistics books due to many options, updates, and changes in statistics technology.  The authors have elected to include instructions for using algorithms embedded in popular models of Texas Instruments calculators to perform statistical calculations.  The selected models have been popular for decades and will likely have continued longevity.  Online versions of these calculators are also available for convenience and are free, consistent with the concept of open-access textbooks.  All of this contributes to a high rating for relevance.  On the other hand, entering and manipulating data manually on a calculator is different from how data are typically handled using statistical software in real life statistics applications.  The choice of statistics technology in this book is convenient for learning statistical concepts, but lacks some relevance to how researchers actually analyze data.","clarity_rating":5,"clarity_review":"The language is simple and clear.  Immediate examples are provided to clarify definitions and general explanations.  The solution sheets in the appendix are particularly useful for guiding students through the many steps in conducting a hypothesis test.","consistency_rating":5,"consistency_review":"I found very few minor inconsistencies that were pedagogically inconsequential.","modularity_rating":5,"modularity_review":"Not only is the textbook available as a single pdf download, but individual links are available for each section.  This makes it particularly easy to embed links for the desired sections into an online course for quick reference.","organization_rating":5,"organization_review":"Correlation and regression are presented near the end of the book, just before ANOVA.  This makes sense in terms of covering the General Linear Model as a unit, but differs from other applied statistics texts that teach correlation and descriptive regression prior to hypothesis testing.","interface_rating":5,"interface_review":"I tried a number of links in the footnotes, including links to individual written sections, exercises, and videos.  All worked well.  This feature is particularly amenable to embedding the individual links into an online course.","grammatical_rating":5,"grammatical_review":"The language is simple and clear.  I found no grammatical errors.","cultural_rating":5,"cultural_review":"The book begins with an open letter to the student.  The letter explains the values and best practices for the course, rather than assuming familiarity.  This is helpful for students entering the course with a variety of backgrounds and initial attitudes toward statistics.  The section on English phrases written mathematically is particularly considerate not only of students who are nonnative speakers of English, but also those with learning differences and students with weak math backgrounds.","overall_rating":10,"overall_review":"This text is pedagogically thoughtful and provides many useful instructional resources.","created_at":"2021-03-31T12:06:24.000-05:00","updated_at":"2021-03-31T12:06:24.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/collaborative-statistics","updated_at":"2026-05-18T02:10:19.000-05:00"},{"id":21,"title":"Introduction to Probability","edition_statement":"2nd edition","volume":null,"copyright_year":2006,"isbn10":null,"isbn13":null,"license":"Free Documentation License (GNU)","language":"eng","accessibility_statement":null,"accessibility_features":[],"description":"Probability theory began in seventeenth century France when the two great French mathematicians, Blaise Pascal and Pierre de Fermat, corresponded over two problems from games of chance. Problems like those Pascal and Fermat solved continuedto influence such early researchers as Huygens, Bernoulli, and DeMoivre in establishing a mathematical theory of probability. Today, probability theory is a wellestablished branch of mathematics that finds applications in every area of scholarlyactivity from music to physics, and in daily experience from weather prediction topredicting the risks of new medical treatments. This text is designed for an introductory probability course taken by sophomores,juniors, and seniors in mathematics, the physical and social sciences, engineering,and computer science. It presents a thorough treatment of probability ideas andtechniques necessary for a form understanding of the subject. The text can be usedin a variety of course lengths, levels, and areas of emphasis. For use in a standard one-term course, in which both discrete and continuousprobability is covered, students should have taken as a prerequisite two terms ofcalculus, including an introduction to multiple integrals. In order to cover Chapter 11, which contains material on Markov chains, some knowledge of matrix theoryis necessary. The text can also be used in a discrete probability course. The material has beenorganized in such a way that the discrete and continuous probability discussions arepresented in a separate, but parallel, manner. This organization dispels an overlyrigorous or formal view of probability and o?ers some strong pedagogical valuein that the discrete discussions can sometimes serve to motivate the more abstractcontinuous probability discussions. For use in a discrete probability course, studentsshould have taken one term of calculus as a prerequisite. Very little computing background is assumed or necessary in order to obtain fullbenefits from the use of the computing material and examples in the text. All ofthe programs that are used in the text have been written in each of the languagesTrueBASIC, Maple, and Mathematica.","contributors":[{"id":3758,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Charles","middle_name":"M.","last_name":"Grinstead","location":"Swarthmore College","background_text":"Charles M. Grinstead, Professor, Department of Mathematics and Statistics, Swarthmore College."},{"id":3759,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"J. Laurie","middle_name":null,"last_name":"Snell","location":"Dartmouth College","background_text":"James Laurie Snell, often cited as J. Laurie Snell, was an American mathematician. A graduate of the University of Illinois, he taught at Dartmouth College until retiring in 1995."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":13,"name":"Engineering \u0026 Technology","parent_subject_id":null,"call_number":"TA145","visible_textbooks_count":119,"url":"https://open.umn.edu/opentextbooks/%20/subjects/engineering"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":3,"url":"http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html","year":null,"created_at":"2018-09-07T12:22:36.000-05:00","updated_at":"2018-09-07T12:22:36.000-05:00","name":"American Mathematical Society"}],"formats":[{"id":6,"type":"PDF","url":"https://math.dartmouth.edu/~prob/prob/prob.pdf","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":7,"type":"Hardcopy","url":"https://bookstore.ams.org/iprob-s","price":{"cents":6000,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":6,"reviews":[{"id":248,"first_name":"Tomasz","last_name":"Gorecki","position":"Visiting Professor","institution_name":"Colorado State University","comprehensiveness_rating":5,"comprehensiveness_review":"The book consists of 12 chapters, 3 appendices with tables and index. It is designed for an introductory probability course, for use in a standard one-term course, in which both discrete and continuous probability is covered. This book covers a little bit more than I would normally cover in a probability class (Markov chains and random walks) and omits nothing that I would normally cover. All subject areas address in the Table of Contents are covered thoroughly.","accuracy_rating":5,"accuracy_review":"The book is mathematically accurate as far as I can tell. Examples are worked out in full detail throughout the text. In the earlier version were some mistakes, but have been corrected (errata is available on the website). All of these errors have been corrected in the current web version.","relevance_rating":5,"relevance_review":"The content is as up-to-date as any introductory probability textbook can reasonably be. In terms of longevity, the fact that the text of the book is stored in LaTeX ensures that the text will be useful for a long time to come. Updates will be straightforward to implement. There are over 600 exercises in the text. There are exercises to be done with and without the use of a computer and more theoretical exercises. A solution manual is available to instructors from website (odd-numbered exercices) or from the authors. In the text the computer is utilized in several ways: simulation, graphical illustration and to solve problems that do not lend to closed-form formulas. All programs used in the text have been written in TrueBASIC, Maple, and Mathematica. ","clarity_rating":5,"clarity_review":"I think that the text in this book is extremely clear, which is great for a first course in probability. It helps a large number of figures illustrating the discussed ideas. Authors have tried to present probability without too much formal mathematics but without sacrificing rigor. They have tried to develop the key ideas to provide a variety of interesting applications in normal live. ","consistency_rating":5,"consistency_review":"The text is consistent in its terminology, both internally and globally.","modularity_rating":4,"modularity_review":"The text is divided into small subsections with separate exercices for students to read (there are easily be used as modules). ","organization_rating":4,"organization_review":"The organization is fine. The book presents all the topics in an appropriate sequence.  I expect that instructors using this book would be using the material in the presented order (maybe Combinatorics first).","interface_rating":3,"interface_review":"The interface is OK. I didn't experience any problems. The lack of color graphics even in digital version (few times authors use light blue color). I reviewed using the pdf version of the book. This does not have a linked table of contents, which would allow direct access to the sections. I wish the pdf file had this functionality. The lack of hyperlinks is somewhat troublesome.","grammatical_rating":5,"grammatical_review":"I found no grammatical errors in this textbook (but English is not my native language). It is very well written.","cultural_rating":5,"cultural_review":"No portion of this text appeared to me to be culturally insensitive or offensive in any way, shape, or form.","overall_rating":9,"overall_review":"I think that this textbook provides a great introduction to probability! With such textbook available to students for free, I do not see any reasons to force my students to purchase a different textbook. My only complaint concerns the software. I would have preferred programs to be written in the language R.\r\n\r\nThere are numerous very interesting historical comments in the text.","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":846,"first_name":"Huimin","last_name":"Chen","position":"associate professor","institution_name":"University of New Orleans","comprehensiveness_rating":4,"comprehensiveness_review":"The book covers the fundamentals of probability theory with quite a few practical engineering applications, which seems appropriate for engineering students to connect the theory to the practice. Each chapter contains realistic examples that apply probability theory to basic statistical inference and naturally connect to the Monte Carlo simulations and graphical illustration of the probability distributions and probability density functions. Students with basic calculus and discrete math can easily follow the development of probabilistic modeling and important properties of the popularly used probability distributions. Only the ergodic Markov chain and random walk appear challenging for the undergraduate students to comprehend without the formal introduction of stochastic process.","accuracy_rating":5,"accuracy_review":"I do no see any apparent error in the examples covered by this book.","relevance_rating":4,"relevance_review":"The book can serve as an introduction of the probability theory to engineering students and it supplements the continuous and discrete signals and systems course to provide a practical perspective of signal and noise, which is important for upper level courses such as the classic control theory and communication system design. The material seems up-to-date and may be appealing to students with experience of Matlab to simulate various random events including the Markov chain and random walk covered in the later chapters.","clarity_rating":5,"clarity_review":"The book is well written with many interesting exercise problems for students to enhance their understanding. It would be nice to provide a few solutions to the selected problems.","consistency_rating":5,"consistency_review":"The terminology and framework used in the book are consistent.","modularity_rating":5,"modularity_review":"The book can be divided and/or regrouped easily to fit the need for self-study. The discrete and continuous random variables and popularly used distributions can be summarized in separate tables (e.g., putting in the appendix). ","organization_rating":4,"organization_review":"The book is well organized with coherent logical development. It would be nice to add a brief introduction to continuous time and discrete time stochastic processes before introducing the Markov chain and random walk.","interface_rating":4,"interface_review":"The book has many index terms but not available for click-through in the electronic format.","grammatical_rating":5,"grammatical_review":"I do not see any grammatical problem.","cultural_rating":5,"cultural_review":"I do not see any cultural issue in the examples used to demonstrate the probability theory.","overall_rating":9,"overall_review":"This is a very nice introduction book to probability theory without using axiomatic and/or set theoretic coverage of the probability. It contains many interesting examples to demonstrate how to apply a probabilistic modeling or statistical procedure to study the real world phenomena. The integration with some software (such as Matlab) would provide better visualization of the random events, distribution and statistical properties of the random variable/process. ","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":1210,"first_name":"Hasan","last_name":"Hamdan","position":"Professor of Statistics","institution_name":"James Madison University","comprehensiveness_rating":4,"comprehensiveness_review":"The book covers all areas in a typical introductory probability course. The course would be appropriate for seniors in mathematics or statistics or data science or computer science. It is also appropriate for first year  graduate students in any of these fields.","accuracy_rating":5,"accuracy_review":"The book is very accurate.","relevance_rating":5,"relevance_review":"Content is up-to-date. In fact, the way simulations are used to illustrate important concepts in probability and statistics \n is now more relevant that ever ! the emerging focus on computing and computing-related areas like the field of Data Science and Data Analytics or Big Data makes this book and important textbook or resource. So, this is the right book or resource and No Need to Re-invent the Wheel!!!!","clarity_rating":5,"clarity_review":"The book is very clear and smooth. Everything is classic or traditional except few places where I noticed a difference of what I am used to see: the authors used a unique notation, m(x),  for the  distribution function (cdf)  in the discrete case compared to that for the continuous case.  Also,I am not sure that  the selected  vector and complement notations  are commonly used.","consistency_rating":5,"consistency_review":"The book is consistent and the material flows nicely! the important concepts are introduced and revisited many times  and sometimes different ways! I love the connection made with other areas! I love the use of Paradoxes.","modularity_rating":5,"modularity_review":"Modularity is another major strength of the book! Although the material is nicely connected but but once can easily select to cover certain parts and skip others without creating  gaps or difficulties in the students leering. The flow of the coverage and   the nature of the probability area help in this matter.  \nYou can easily treat or cover the discrete random variables separately and select the related material without any difficulties. You can do the same thing for the continuous case. You can leave some of the challenging examples that include some of the paradoxes that maybe challenging for students! \nYou can also easily and smoothly teach or assign the history and development of the selected  topics as reading s without making it as a part of the graded  course!","organization_rating":4,"organization_review":"Overall, the material is presented in a smooth way! but that is not necessarily the order I would go with when i cover these topics.\nOf course that is a matter of style, depending on the audience, I think it is easier to teach the material in Ch10 (moment generating functions), then may be add a section about movements.   I would probably slightly  modify it. I would point at few other things later!","interface_rating":5,"interface_review":"The book is free of any interface issues.","grammatical_rating":5,"grammatical_review":"No grammatical errors","cultural_rating":5,"cultural_review":"The book is written with examples and problems  that are very relevant to the culture we are in. Examples form the business world (examples include insurance coverage and insurance-related problems, gambling and lottery, sports, etc.)","overall_rating":10,"overall_review":"Yes, I  have specific comments that maybe useful to the authors: \nFirst: Thank you:\nThank you for writing such a  wonderful book.  It is very clear,  that the standards you held are really high and the timing of the book is unbelievable appropriate!  with the new emerging  statistical fields, this book should be used in the core courses!\n\nSecond: I have few specific suggestions/few typos  that maybe useful. If you are interested, please let me know.","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":1299,"first_name":"Steve","last_name":"Schoenbaechler","position":"Instructor","institution_name":"Miami University (Ohio)","comprehensiveness_rating":4,"comprehensiveness_review":"There is a table of contents that breaks up the chapters into subtopics, also.  There is an index.  Not much depth in some areas.  There isn't much talked about with certain graphics, aka defining histograms and pie charts.  Hypothesis testing is limited.  There are no solutions in the back of the book to the chapter problems.  Correlation?  Probability is covered well.  Statistics (aka Prob and Stats)?","accuracy_rating":5,"accuracy_review":"The book does seem to be free of errors.","relevance_rating":5,"relevance_review":"The book's relevance and longevity shouldn't be a problem.  All information is relevant to the topic.  I read the online version.  So, one would think that any updates would be rather easily accomplished.","clarity_rating":3,"clarity_review":"The book wasn't very clear for me.  I noticed several times where, for example, individual cases were listed simply within the formatting of the paragraph, where these should probably be outlined, with bullet-points.  Or, definitions are given within the framework of the paragraphs, where these should probably be separated from the paragraph, given their own spaces in the text.  Even though important terms may be italicized, it can still be difficult to identify them within the readings.  Some of the symbols, you have to take your time to make sure you understand just what it is describing.","consistency_rating":5,"consistency_review":"The textbook does seem to be consistent in its use of terminology and framework.  It does show consistent structure, rather than going \"hodge podge\" every once in a while.","modularity_rating":4,"modularity_review":"Each chapter in the book does show suptopics on the table of contents.  As for re-ordering the chapters, that may have something to do with how the individual instructor conducts the class.  As in, if the instructor re-orders the material, they are probably going to have to provide some of their own introduction material for each chapter.","organization_rating":3,"organization_review":"The flow tends to be a bit tedious at times.  Some steps and/or terms are written in the format of the paragraphs, themselves, and not set apart from the rest of the writing.","interface_rating":3,"interface_review":"The interface is decent.  Some of the charts and tables are 2-4 pages off.  But, the way the author did many of the graphics, he grouped many of the graphics together on certain pages.  Computer programs are mentioned throughout the examples, but there are no computer codes or programs listed anywhere.","grammatical_rating":5,"grammatical_review":"The book's grammar was fine.  Very well written in this aspect.","cultural_rating":5,"cultural_review":"There are seemingly no distinguishing cultural insensitivities.","overall_rating":8,"overall_review":"I felt this textbook could do more.  For the price, free, you can't beat it.  However, considering as a student, to prepare me for future coursework and work on the job, I believe this textbook leaves much out.  I remember taking a course with a book like this; I had to end up taking a separate Statistics class, also, because the course was certain statistics work.  A lot of the symbolism comes up on you right away; you really have to take the time to understand the meaning of it.  The missing information could be covered by a good instructor, but then there wouldn't be a need for a textbook in those parts.  With as many times computer programs were referenced, it would have been nice to actually see the code for these programs at times, at least.","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":1629,"first_name":"XIAOQIAN","last_name":"SUN","position":"Professor","institution_name":"Clemson University","comprehensiveness_rating":4,"comprehensiveness_review":"The book covers all subjects that I need except the required materials on joint distributions. It would be great to have two more chapters to cover joint probability distributions for discrete and continuous random variables. Also I feel that the last chapter on random walks is not necessary to be included.","accuracy_rating":5,"accuracy_review":"It does seem to be free of errors","relevance_rating":5,"relevance_review":"Yes, the content is up-to-date and the book with adding some materials on joint distributions is good to serve as an introduction of probability for undergraduates.","clarity_rating":5,"clarity_review":"well written and with a lot of interesting examples and exercise problems.","consistency_rating":5,"consistency_review":"yes, the terminology and framework in this book are consistent ","modularity_rating":4,"modularity_review":"I would like to move CH3 on combinatorics to the front  before talking about any distribution in CH1 and CH2. Also CH5 on some important distributions could be split to CH1 and CH2.  ","organization_rating":4,"organization_review":"The book is well organized but could be better with some changes, see my comments in Item 6 above ","interface_rating":4,"interface_review":"index terms on the back could be improved with some click-through function.","grammatical_rating":5,"grammatical_review":"I do not see grammatical problem (I am not a native speaker)","cultural_rating":5,"cultural_review":"no cultural issues found in the book","overall_rating":9,"overall_review":"This is a good introduction book on probability, especially it is free to students. I hope that the authors could update the book soon with considering my suggestions ","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":2460,"first_name":"Jim","last_name":"Burns","position":"Assistant Professor of Industrial Engineering","institution_name":"Western Michigan University","comprehensiveness_rating":4,"comprehensiveness_review":"This text provides very good coverage of the essential topics for an introductory probability course in addition to its coverage of topics that I’m sure are left out of some introductory courses such as Markov processes and generating functions.  The strength of this book in my view (which is from an engineering perspective) is that it approaches topics in a very natural way, using practical examples, simple graphics, and discussion of computer simulation when introducing topics.  It does not seem to burden the reader with statistical jargon or needlessly deep discussions of theory, but it does not give the impression that it is trying to avoid these things either.  In my opinion, the book omits all the right things, including most of the tables found in introductory probability and statistics texts.  The book is well-organized as any good textbook should be.  The table of contents, index, and preface are all helpful.","accuracy_rating":5,"accuracy_review":"While there are far too many examples and problems to check every one, I found no errors in the problems and examples I did work through.  A closer review of what I consider to be essential content also revealed no errors.  I would consider the content to be accurate.","relevance_rating":5,"relevance_review":"The content is up-to-date and on-par with other books on the subject that are used in the engineering discipline.  The addition of computer simulation examples does not detract from its relevance or longevity at all because it is approached in a very general manner, likely making transition between disciplines and over time easier.  I use computer simulation when teaching probability, but would not use the programs used by the authors.  This fact would not deter me from adopting the text.","clarity_rating":5,"clarity_review":"The greatest strength of this book in my view is its clarity.  The examples are presented in a logical way and the writing style is not a burden.  It is also very concise, making it easy to digest the material.  Formulae are presented simply (for an audience with the appropriate background) with clear explanations in the text.","consistency_rating":5,"consistency_review":"The terminology, writing style, and logical development of concepts is consistent throughout.  The coverage of topics also seems to be balanced, not favoring deeper treatment of only some topics.  Other introductory texts I have experience with seem to trail-off when it comes to the more advanced topics.","modularity_rating":5,"modularity_review":"The chapters seem to be compact and self-contained, making it possible to progress through the material in an order other than listed in the table of contents.  The separation of chapter 10 (Generating Functions) and chapter 5 (Distribution and Densities) is a refreshing change from other textbooks I have used and helps with the modularity a great deal.","organization_rating":5,"organization_review":"The flow of the book is very logical, but does present topics in a slightly different order than I would in a classroom.  Fortunately, the modularity of the book is good, which gives instructors the freedom to choose the flow that works best for them.  ","interface_rating":4,"interface_review":"I found no problems with the text, graphics, or other aspects.  It just seems like a normal book.  It does not have more advanced features that are common in “online” textbooks such as hyperlinks and imbedded content.  I do not find this problematic, but some may.","grammatical_rating":5,"grammatical_review":"I do not recall any grammatical errors in my reading nor did I make notes of any errors as I worked my way through the book.","cultural_rating":5,"cultural_review":"The book is written in an accessible way.  Its examples are relatable, but not trivial, and does not broach topics in a way that could be viewed as offensive.  More importantly, understanding the examples does not seem like it would be predicated on having a deep understanding of a particular subject matter (e.g., engineering) or culture.","overall_rating":10,"overall_review":"Of the probability and statistics books I have used, I consider this to be one of the better ones for explaining difficult probability concepts clearly.  I prefer not to be constrained to a specific textbook (and therefore a specific style) when teaching a class.  Happily, I feel this book would not be constraining at all and would support many teaching styles and instructional approaches to introductory probability.  I especially like the numerous exercises.  At a minimum, I intend to begin using this textbook as a reference in my course immediately, with the expectation of making it the primary textbook in the very near future.","created_at":"2018-12-13T11:40:34.000-06:00","updated_at":"2018-12-13T11:40:34.000-06:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/introduction-to-probability","updated_at":"2026-05-18T12:03:48.000-05:00"},{"id":60,"title":"OpenIntro Statistics","edition_statement":"Fourth Edition","volume":null,"copyright_year":2019,"isbn10":null,"isbn13":null,"license":"Attribution-ShareAlike","language":"eng","accessibility_statement":null,"accessibility_features":null,"description":"OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to appliedstatistics that is clear, concise, and accessible. This book was written with the undergraduate levelin mind, but it’s also popular in high schools and graduate courses.We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. • Statistics is an applied field with a wide range of practical applications.• You don’t have to be a math guru to learn from real, interesting data.• Data are messy, and statistical tools are imperfect. But, when you understand the strengthsand weaknesses of these tools, you can use them to learn about the world.","contributors":[{"id":3129,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"David","middle_name":"M.","last_name":"Diez","location":"Harvard School of Public Health","background_text":"David M. Diez is a Quantitative Analyst at Google where he works with massive data sets and performs statistical analyses in areas such as user behavior and forecasting."},{"id":3130,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Christopher","middle_name":"D.","last_name":"Barr","location":"Harvard School of Public Health","background_text":"Christopher D. Barr is an Assistant Research Professor with the Texas Institute for Measurement, Evaluation, and Statistics at the University of Houston."},{"id":3131,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Mine","middle_name":null,"last_name":"Cetinkaya-Rundel","location":"Duke University","background_text":"Mine Cetinkaya-Rundel is the Director of Undergraduate Studies and Assistant Professor of the Practice in the Department of Statistical Science at Duke University."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":510,"url":"https://www.openintro.org/stat/textbook.php?stat_book=os","year":2019,"created_at":"2018-09-07T12:22:40.000-05:00","updated_at":"2020-08-19T16:45:25.000-05:00","name":"OpenIntro"}],"formats":[{"id":489,"type":"PDF","url":"https://www.openintro.org/go/?id=os4_for_screen_readers\u0026referrer=/book/os/index.php","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":490,"type":"Hardcopy","url":"https://www.amazon.com/OpenIntro-Statistics-Fourth-Full-Color/dp/1943450080/ref=as_li_ss_tl?dchild=1\u0026keywords=openintro+color\u0026qid=1593060405\u0026s=books\u0026sr=1-1\u0026linkCode=sl1\u0026tag=openintroorg-20\u0026linkId=f8ada1dbb847ff96f17818701129816d\u0026language=en_US","price":{"cents":902,"currency_iso":"USD"},"isbn":null},{"id":491,"type":"Hardcopy","url":"https://www.amazon.com/OpenIntro-Statistics-Fourth-David-Diez-dp-1943450072/dp/1943450072/ref=mt_other?_encoding=UTF8\u0026me=\u0026qid=1593060405","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":24,"reviews":[{"id":89,"first_name":"Bo","last_name":"Hu","position":"Assistant Professor","institution_name":"University of Minnesota","comprehensiveness_rating":2,"comprehensiveness_review":"This book covers topics in a traditional curriculum of an introductory statistics course: probabilities, distributions, sampling distribution, hypothesis tests for means and proportions, linear regression, multiple regression and logistic regression. While the traditional curriculum does not cover multiple regression and logistic regression in an introductory statistics course, this book offers the information in these two areas. The book started with several examples and case study to introduce types of variables, sampling designs and experimental designs (chapter 1). It would be nice if the authors can start with the big picture of how people perform statistical analysis for a data set. Chapter 2 covers the knowledge of probabilities including the definition of probability, Law of Large Numbers, probability rules, conditional probability and independence and linear combinations of random variables. However, the linear combination of random variables is too much math focused and may not be good for students at the introductory level. Chapter 3 covers random variables and distributions including normal, geometry and binomial distributions. Chapter 4-6 cover the inferences for means and proportions and the Chi-square test. Chapter 7 and 8 cover the linear , multiple and logistic regression. The book used plenty of examples and included a lot of tips to understand basic concepts such as probabilities, p-values and significant levels etc. The book provides an effective index. The drawback of this book is that it does not cover how to use any computer software or even a graphing calculator to perform the calculations for inferences. All of the calculations covered in this book were performed by hand using the formulas. As the trend of analysis, students will be confronted with the needs to use computer software or a graphing calculator to perform the analyses. Calculations by hand are not realistic.","accuracy_rating":4,"accuracy_review":"The content of the book is accurate and unbiased. However, when introducing the basic concepts of null and alternative hypotheses and the p-value, the book used different definitions than other textbooks. For example, when introducing the p-value, the authors used the definition \"the probability of observing data at least as favorable to the alternative hypothesis as our current data set, if the null hypothesis is true.\" The wording \"at least as favorable to the alternative hypothesis as our current data\" is misleading. Students can easily get confused and think the p-value is in favor of the alternative hypothesis.","relevance_rating":3,"relevance_review":"The content that this book focuses on is relatively stable and so changes would be few and far between. The content is up-to-date. Especially, this book covers Bayesian probabilities, false negative and false positive calculations. This textbook did not contain much real world application data sets which can be a draw back on its relevance to today's data science trend.","clarity_rating":5,"clarity_review":"The text is written in lucid, accessible prose, and provides plenty of examples for students to understand the concepts and calculations. The text also provides enough context for students to understand the terminologies and definitions, especially this textbook provides plenty of tips for each concept and that is very helpful for students to understand the materials.","consistency_rating":5,"consistency_review":"The text is quite consistent in terms of terminology and framework. The organization for each chapter is also consistent.","modularity_rating":5,"modularity_review":"The text is easily and readily divisible into subsections. Each chapter contains short sections and each section contains small subsections. The text is easily reorganized and re-sequenced. The later chapters (chapter 4-8) are self-contained and can be re-ordered. The later chapters (chapters 4-8) are built upon the knowledge from the former chapters (chapters 1-3).","organization_rating":3,"organization_review":"The overall organization of the text is logical. The later chapters on inferences and regression (chapters 4-8) are built upon the former chapters (chapters 1-3). But there are instances where similar topics are not arranged very well: 1) when introducing the sampling distribution in chapter 4, the authors should introduce both the sampling distribution of mean and the sampling distribution of proportion in the same chapter. The authors spend many pages on the sampling distribution of mean in chapter 4, but only a few sentences on the sampling distribution of proportion in chapter 6; 2) the authors introduced independence after talking about the conditional probability. Introducing independence using the definition of conditional probability P(A|B)=P(A) is more accurate and easier for students to understand. The order of introducing independence and conditional probability should be switched. The approach of introducing the inferences of proportions and the Chi-square test in the same chapter is novel. The students can easily see the connections between the two types of tests.","interface_rating":5,"interface_review":"The text is free of significant interface issues. The graphs and tables in the text are well designed and accurate. These graphs and tables help the readers to understand the materials well, especially most of the graphs are colored figures.","grammatical_rating":5,"grammatical_review":"The text contains no grammatical errors.","cultural_rating":5,"cultural_review":"There is no evidence that the text is culturally insensiteve or offensive. Some examples are related to United States. Most of the examples are general and not culturally related. The text offered quite a lot of examples in the medical research field and that is probably related to the background of the authors.","overall_rating":8,"overall_review":"Overall, this is a well written book for introductory level statistics. The text provides enough examples, exercises and tips for the readers to understand the materials. It also offered enough graphs and tables to facilatate the reading. The drawbacks of the textbook are: 1) it doesn't offer how to use of any computer software or graphing calculator to perform the calculations and analyses; 2) it didn't offer any real world data analysis examples.","created_at":"2014-07-15T19:00:00.000-05:00","updated_at":"2014-07-15T19:00:00.000-05:00"},{"id":92,"first_name":"Paul","last_name":"Goren","position":"Professor","institution_name":"University of Minnesota","comprehensiveness_rating":3,"comprehensiveness_review":"This text provides decent coverage of probability, inference, descriptive statistics, bivariate statistics, as well as introductory coverage of the bivariate and multiple linear regression model and logistics regression. Although there are some materials on experimental and observational data, this is, first and foremost, a book on mathematical and applied statistics. Professors looking for in-depth coverage of research methods and data collection techniques will have to look elsewhere. The coverage of probability and statistics is, for the most part, sound. Most essential materials for an introductory probability and statistics course are covered. The authors do a terrific job in chapter 1 introducing key ideas about data collection, sampling, and rudimentary data analysis. Chapters 4-6 on statistical inference are especially strong, and the discussion of outliers and leverage in the regression chapters should prove useful to students who work with small n data sets. Teachers might quibble with a particular omission here or there (e.g., it would be nice to have kernel densities in chapter 1 to complement the histogram graphics and some more probability distributions for continuous random variables such as the F distribution), but any missing material could be readily supplemented. In other cases I found the omissions curious. For instance, the text shows students how to calculate the variance and standard deviation of an observed variable's distribution, but does not give the actual formula. As well, the authors define probability but this is not connected as directly as it could be to the 3 fundamental axioms that comprise the mathematical definition of probability. The authors limit their discussion on categorical data analysis to the chi square statistic, which centers on inference rather than on the substantive magnitude of the bivariate relationship. I wish they included measures of association for categorical data analysis that are used in sociology and political science, such as gamma, tau b and tau c, and Somers d. Finally, I think the book needs to add material on the desirable properties of statistical estimators (i.e., unbiasedness, efficiency, consistency). Appendix A contains solutions to the end of chapter exercises. The index is decent, but there is no glossary of terms or summary of formula, which is disappointing.","accuracy_rating":4,"accuracy_review":"From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.","relevance_rating":4,"relevance_review":"Statistical methods, statistical inference and data analysis techniques do change much over time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book and that omitted materials are added into subsequent editions.","clarity_rating":5,"clarity_review":"The book is clear and well written. All of the chapters contain a number of useful tips on best practices and common misunderstandings in statistical analysis. There are also a number of exercises embedded in the text immediately after key ideas and concepts are presented. I suspect these will prove quite helpful to students. The authors also make GREAT use of statistical graphics in all the chapters. Overall, the book is heavy on using ordinary language and common sense illustrations to get across the main ideas. They draw examples from sources (e.g., The Daily Show, The Colbert Report) and daily living (e.g., Mario Kart video games) that college students will surely appreciate. There are no proofs that might appeal to the more mathematically inclined. There are lots of great exercises at the end of each chapter that professors can use to reinforce the concepts and calculations appearing in the chapter. I also appreciated that the authors use examples from the hard sciences, life sciences, and social sciences. This will increase the appeal of the text.","consistency_rating":5,"consistency_review":"The book is very consistent from what I can see.","modularity_rating":4,"modularity_review":"This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class. Things flow together so well that the book can be used as is.","organization_rating":5,"organization_review":"The organization is fine. The book presents all the topics in an appropriate sequence.","interface_rating":5,"interface_review":"The interface is fine. I didn't experience any problems. The color graphics come through clearly and the embedded links work as they should.","grammatical_rating":5,"grammatical_review":"I didn't see any errors, it looks fine.","cultural_rating":5,"cultural_review":"The book is not culturally offensive.","overall_rating":9,"overall_review":"Teachers looking for a text that they can use to introduce students to probability and basic statistics should find this text helpful. It might be asking too much to use it as a standalone text, but it could work very well as a supplement to a more detailed treatment or in conjunction with some really good slides on the various topics. I think it would work well for liberal arts/social science students, but not for economics/math/science students who would need more mathematical rigor.","created_at":"2014-07-15T19:00:00.000-05:00","updated_at":"2014-07-15T19:00:00.000-05:00"},{"id":115,"first_name":"Paul","last_name":"Murtaugh","position":"Associate Professor","institution_name":"Oregon State University","comprehensiveness_rating":3,"comprehensiveness_review":"The text has a thorough introduction to data exploration, probability, statistical distributions, and the foundations of inference, but less complete discussions of specific methods, including one- and two-sample inference, contingency tables, and linear and logistic regression. Supposedly intended for \"introductory statistics courses at the high school through university levels\", it's not clear where this text would fit in at my institution. It includes too much theory for our undergraduate service courses, but not enough practical details for our graduate-level service courses.","accuracy_rating":4,"accuracy_review":"The text is mostly accurate, especially the sections on probability and statistical distributions, but there are some puzzling gaffes. For example, it is claimed that the Poisson distribution is suitable only for rare events (p. 148); the unequal-variances form of the standard error of the difference between means is used in conjunction with the t-distribution, with no mention of the need for the Satterthwaite adjustment of the degrees of freedom (p. 231); and the degrees of freedom in the chi-square goodness-of-fit test are not adjusted for the number of estimated parameters (p. 282).","relevance_rating":3,"relevance_review":"Some of the content seems dated. For example, there is a strong emphasis on assessing the normality assumption, even though most of the covered methods work well for non-normal data with reasonable sample sizes. Normal approximations are presented as the tool of choice for working with binomial data, even though exact methods are efficiently implemented in modern computer packages. Fisher's exact test is not even mentioned. The section on model selection, covering just backward elimination and forward selection, seems especially old-fashioned.","clarity_rating":3,"clarity_review":"The prose is sometimes tortured and imprecise. For example: \"Researchers perform an observational study when they collect data in a way that does not directly interfere with how the data arise\" (p. 13). \"Standard error\" is defined as the \"standard deviation associated with an estimate\" (p. 163), but it is often unclear whether population or sample-based quantities are being referred to. Use of the t-distribution is motivated as a way to \"resolve the problem of a poorly estimated standard error\", when really it is a way to properly characterize the distribution of a test statistic having a sample-based standard error in the denominator.","consistency_rating":3,"consistency_review":"As in many/most statistics texts, it is a challenge to understand the authors' distinction between \"standard deviation\" and \"standard error\". The title of Chapter 5, \"Inference for numerical data\", took me by surprise, after the extensive use of numerical data in the discussion of inference in Chapter 4. Some topics seem to be introduced repeatedly, e.g., the Central Limit Theorem (pp. 167, 185, and 222) and the comparison of two proportions (pp. 191 and 268). The authors are sloppy in their use of hat notation when discussing regression models, expressing the fitted value as a function of the parameters, instead of the estimated parameters (pp. 325 and 357).","modularity_rating":4,"modularity_review":"The text includes sections that could easily be extracted as modules. For example, I can imagine using pieces of Chapters 2 (Probability) and 3 (Distributions of random variables) to motivate methods that I discuss in service courses.","organization_rating":3,"organization_review":"Chapters 1 through 4, covering data, probability, distributions, and principles of inference flow nicely, but the remaining chapters seem like a somewhat haphazard treatment of some commonly used methods. One-way analysis of variance is introduced as a special topic, with no mention that it is a generalization of the equal-variances t-test to more than two groups. The final chapter (8) gives superficial treatments of two huge topics, multiple linear regression and logistic regression, with insufficient detail to guide serious users of these methods. It is as if the authors ran out of gas after the first seven chapters and decided to use the final chapter as a catchall for some important, uncovered topics.","interface_rating":5,"interface_review":"The interface is nicely designed. The availability of data sets and functions at a website (www.openintro.org) and as an R package (cran.r-project.org/web/packages/openintro) is a huge plus that greatly increases the usefulness of the text.","grammatical_rating":3,"grammatical_review":"There are distracting grammatical errors. \"Data\" is sometimes singular, sometimes plural in the authors' prose. Other examples: \"Each of the conclusions are based on some data\" (p. 9); \"You might already be familiar with many aspects of probability, however, formalization of the concepts is new for most\" (p. 68); and \"Sometimes two variables is one too many\" (p. 21).","cultural_rating":3,"cultural_review":"I have no idea how to characterize the cultural relevance of a statistics textbook.","overall_rating":7,"overall_review":"In my opinion, the text is not a strong candidate for an introductory textbook for typical statistics courses, but it contains many sections (particulary on probability and statistical distributions) that could profitably be used as supplemental material in such courses.","created_at":"2014-07-15T19:00:00.000-05:00","updated_at":"2014-07-15T19:00:00.000-05:00"},{"id":563,"first_name":"Monte","last_name":"Cheney","position":"Associate Professor of Mathematics","institution_name":"Central Oregon Community College","comprehensiveness_rating":4,"comprehensiveness_review":"More depth in graphs: histograms especially. Percentiles? Also, non-parametric alternatives would be nice, especially Monte Carlo/bootstrapping methods.","accuracy_rating":5,"accuracy_review":"The most accurate open-source textbook in statistics I have found. Though I might define p-values and interpret confidence intervals slightly differently. I did not see much explanation on what it means to fail to reject Ho. I would consider this \"omission\" as almost inaccurate.","relevance_rating":3,"relevance_review":"Although accurate, I believe statistics textbooks will increasingly need to incorporate non-parametric and computer-intensive methods to stay relevant to a field that is rapidly changing. Also, as fewer people do manual computations, interpretation of computer software output becomes increasingly important.","clarity_rating":4,"clarity_review":"Quite clear. The text, though dense, is easy to read. More color, diagrams, photos? Marginal notes for key concepts \u0026amp; formulae?","consistency_rating":5,"consistency_review":"No problems here.","modularity_rating":5,"modularity_review":"This textbook is nicely parsed. Especially like homework problems clearly divided by concept.","organization_rating":5,"organization_review":"Great job overall. However, the introduction to hypothesis testing is a bit awkward (this is not unusual). Create a clear way to explain this multi-faceted topic and the world will beat a path to your door.","interface_rating":5,"interface_review":"No problems, but again, the text is a bit dense. Reads more like a 300-level text than 100/200-level. More color, diagrams, etc.?","grammatical_rating":5,"grammatical_review":"I did not encounter any issues.","cultural_rating":4,"cultural_review":"Overall it was not offensive to me, but I am a college-educated white guy. Examples of how statistics can address gender bias were appreciated. It would be nice to see more examples of how statistics can bring cultural/social/economic issues to light (without being heavy handed) would be very motivating to students.","overall_rating":9,"overall_review":"Overall, this is the best open-source statistics text I have reviewed. Most contain glaring conceptual and pedagogical errors, and are painful to read (don't get me started on percentiles or confidence intervals). Also, a reminder for reviewers to save their work as they complete this review would be helpful.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":565,"first_name":"Robin","last_name":"Thomas","position":"Professor","institution_name":"Miami University, Ohio","comprehensiveness_rating":3,"comprehensiveness_review":"The coverage of this text conforms to a solid standard (very classical) semester long introductory statistics course that begins with descriptive statistics, basic probability, and moves through the topics in frequentist inference including basic hypothesis tests of means, categories, linear and multiple regression.  The regression treatment of categorical predictors is limited to dummy coding (though not identified as such) with two levels in keeping with the introductory nature of the text.  There is a bit of coverage on logistic regression appropriate for categorical (specifically, dichotomous) outcome variables that usually is not part of a basic introduction.  Within each appears an adequate discussion of underlying assumptions and a representative array of applications.  Some of the more advanced topics are treated as 'special topics' within the sections (e.g., power and standard error derivations).  Some more modern concepts, such as various effect size measures, are not covered well or at all (for example, eta squared in ANOVA).   However, classical measures of effect such as confidence intervals and R squared appear when appropriate though they are not explicitly identified as measures of effect.","accuracy_rating":5,"accuracy_review":"Technical accuracy is a strength for this text especially with respect to underlying theory and impacts of assumptions.","relevance_rating":3,"relevance_review":"The basics of classical inferential statistics changes little over time and this text covers that ground exceptionally well.  More modern approaches to statistical methods, however, will need to include concepts of important to the current replicability crisis in research:  measures of effect, extensive applications of power analyses, and Bayesian alternatives.  The task of reworking statistical training in response to this crisis will be daunting for any text author not just this one.","clarity_rating":4,"clarity_review":"One of the strengths of this text is the use of motivated examples underlying each major technique.  These examples and techniques are very carefully described with quality graphical and visual aids to support learning.  To many texts that cover basic theory are organized as theorem/proof/example which impedes understanding of the beginner.  This defect is not present here:  this text embraces an 'embodied' view of learning which prioritizes example applications first and then explanation of technique.","consistency_rating":4,"consistency_review":"The consistency of this text is quite good.  Notation, language, and approach are maintained throughout the chapters.","modularity_rating":2,"modularity_review":"It is difficult for a topic that in inherently cumulative to excel at modularity in the manner that is usually understanding.  Each topic builds on the one before it in any statistical methods course.  This text does indicate that some topics can be omitted by identifying them as 'special topics'.","organization_rating":3,"organization_review":"The structure and organization of this text corresponds to a very classic treatment of the topic.  It begins with the basics of descriptive statistics, probability, hypothesis test concepts, tests of numerical variables, categorical, and ends with regression.  I have seen other texts begin with correlation and regression prior to tests of means, etc., and wonder which approach is best.","interface_rating":4,"interface_review":"This is the third edition and benefits from feedback from prior versions.  I found no negative issues with regard to interface elements.  It is a pdf download rather than strictly online so the format is more classical textbook as would be experienced in a print version.","grammatical_rating":5,"grammatical_review":"Typos and errors were minimal (I could find none).","cultural_rating":3,"cultural_review":"It is clear that the largest audience is assumed to be from the United States as most examples draw from regions in the U.S. (e.g., U.S. presidential elections, data from California, data from U.S. colleges, etc.) though some examples come from other parts of the world (Greece economics, Australian wildlife).  The language seems to be free of bias.","overall_rating":7,"overall_review":"This text is an excellent choice for an introductory statistics course that has a broad group of students from multiple disciplines.  The basic theory is well covered and motivated by diverse examples from different fields.   This diversity in discipline comes at the cost of specificity of techniques that appear in some fields such as the importance of measures of effect in psychology.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":748,"first_name":"Emiliano","last_name":"Vega","position":"Mathematics Instructor","institution_name":"Portland Community College","comprehensiveness_rating":5,"comprehensiveness_review":"For a Statistics I course at most community colleges and some four year universities, this text thoroughly covers all necessary topics.  For example, types of data, data collection, probability, normal model, confidence intervals and inference for single proportions.\n\nA thoughtful index is provided at the end of the text as well as a strong library of homework / practice questions at the end of each chapter.\n","accuracy_rating":5,"accuracy_review":"The content is accurate in terms of calculations and conclusions and draws on information from many sources, including the U.S. Census Bureau to introduce topics and for homework sets.\n\nErrors are not found as of yet. The content stays unbiased by constantly reminding the reader to consider data, context and what one’s conclusions might mean rather than being partial to an outcome or conclusions based on one’s personal beliefs in that the conclusions sense that statistics texts give special. Some examples of this include the discussion of anecdotal evidence, bias in data collection, flaws in thinking using probability and practical significance vs statistical significance.\n","relevance_rating":4,"relevance_review":"The text is up to date and the content / data used is able to be modified or updated over time to help with the longevity of the text. For example, a scatterplot involving the poverty rate and federal spending per capita could be updated every year. Another example that would be easy to update and is unlikely to become non-relevant is email and amount of spam, used for numerous topics.\n\nThe probability section uses a data set on smallpox to discuss inoculation, another relevant topic whose topic set could be easily updated.  This selection of topics and their respective data sets are layered throughout the book. The book uses relevant topics throughout that could be quickly updated.\n","clarity_rating":4,"clarity_review":"The writing style and context to not treat students like Phd academics (too high of a reading level), nor does it treat them like children (too low of a reading level). The text meets students at a nice place medium where they are challenged with thoughtful, real situations to consider and how and why statistical methods might be useful.\n\nFor example, a goodness of fit test begins by having readers consider a situation of whether or not the ethnic representation of a jury is consistent with the ethnic representation of the area. The introduction of jargon is easy streamlined in after this example introduction.\n","consistency_rating":5,"consistency_review":"Notation is consistent and easy to follow throughout the text.  The text’s selection for notation with common elements such as p-hat, subscripts, compliments, standard error and standard deviation is very clear and consistent.\n\nTables and graphs are sensibly annotated and well organized. Distributions and definitions that are defined are consistently referenced throughout the text as well as they apply or hold in the situations used.\n","modularity_rating":2,"modularity_review":"Each chapter consists of 5-10 sections.  These sections generally are all under ten page in total.\n\nThis easily allow for small sets of reading on a class to class basis or larger sets of reading over a weekend.\n\nEach section within a chapter build on the previous sections making it easy to align content.\n\nFor example, the inference for categorical data chapter is broken in five main section. Single proportion, two proportions, goodness of fit, test for independence and small sample hypothesis test for proportions. This keeps all inference for proportions close and concise helping the reader stay uninterrupted in the topic.\n","organization_rating":4,"organization_review":"The topics are presented in a logical order with each major topics given a thorough treatment.  The text begins with data collection, followed by probability and distributions of a random variable and then finishing (for a Statistics I course) with inference.\n\nPerhaps an even stronger structure would see all the types of content mentioned above applied to each type of data collection.  That is, do probability and inference topics for a SRS, then do probability and inference for a stratified sample and each time taking your probability and inference ideas further so that they are constantly being built upon, from day one! \n","interface_rating":4,"interface_review":"Navigation as a PDF document is simple since all chapters and subsection within the table of contents are hyperlinked to the respective section.  Graphs and tables are clean and clearly referenced, although they are not hyperlinked in the sections.\n\nThe only visual issues occurs in some graphs, such as on page 40-41, which have maps of the U.S. using color to show “intensity”. However with the print version, which can only show varying scales of white through black, it can be hard to compare “intensity”.\n","grammatical_rating":5,"grammatical_review":"No grammatical errors have been found as of yet.","cultural_rating":3,"cultural_review":"The text would not be found to be culturally insensitive in any way, as a large part of the investigations and questions are introspective of cultures and opinions.  For example, income variations in two cities, ethnic distribution across the country, or synthesis of data from Africa. ","overall_rating":8,"overall_review":"The book has a great logical order, with concise thoughts and sections.  While section are concise they are not limited in rigor or depth (as exemplified by a great section on the \"power\" of a hypothesis test) and numerous case studies to introduce topics.\n\nThe reading of the book will challenge students but at the same time not leave them behind.\n\nOverall I like it a lot.  The best statistics OER I have seen yet.","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":771,"first_name":"Casey","last_name":"Jelsema","position":"Assistant Professor","institution_name":"West Virginia University","comprehensiveness_rating":5,"comprehensiveness_review":"There is one section that is under-developed (general concepts about continuous probability distributions), but aside from this, I think the book provides a good coverage of topics appropriate for an introductory statistics course.","accuracy_rating":5,"accuracy_review":"I did not see any inaccuracies in the book.","relevance_rating":5,"relevance_review":"I do not see introductory statistics content ever becoming obsolete.","clarity_rating":5,"clarity_review":"I think that the book is fairly easy to read. The authors bold important terms, and frequently put boxes around important formulas or definitions. If anything, I would prefer the book to have slightly more mathematical notation.","consistency_rating":5,"consistency_review":"I did not see any problems in regards to the book's notation or terminology. It appears smooth and seamless.","modularity_rating":5,"modularity_review":"The book is broken into small sections for each topic. Any significant rearranging of those sections would be incredibly detrimental to the reader, but that is true of any statistics textbook, especially at the introductory level: Earlier concepts provide the basis for later concepts.","organization_rating":4,"organization_review":"For the most part I liked the flow of the book, though there were a few instances where I would have liked to see some different organization. For example, the Central Limit Theorem is introduced and used early in the inference section, and then later examined in more detail. I would tend to group this in with sampling distributions.\n\nAlso, for how the authors seem to be focusing on practicalities, I was somewhat surprised about some of the organization of the inference sections. The authors use the Z distribution to work through much of the 1-sample inference. The t distribution is introduced much later. I realize this is how some prefer it, but I think introducing the t distribution sooner is more practical. The organization in chapter 5 also seems a bit convoluted to me. The chapter is about \"inference for numerical data\". They authors already discussed 1-sample inference in chapter 4, so the first two sections in chapter 5 are Paired Data and Difference of Means, then they introduce the t-distribution and go back to 1-sample inference for the mean, and then to inference for two means using he t-distribution. It strikes me as jumping around a bit.\n\nOverall the organization is good, so I'm still rating it high, but individual instructors may disagree with some of the order of presentation.","interface_rating":4,"interface_review":"In general I was satisfied. My only complaint in this is that, unlike a number of \"standard\" introductory statistics textbooks I have seen, is that the exercises are organized in a page-wide format, instead of, say, in two columns. I assume this is for the benefit of those using mobile devices to view the book, but scrolling through on a computer, the sections and the exercises tend to blend together. Some more separation between sections, and between text vs. exercises would be appreciated.","grammatical_rating":5,"grammatical_review":"I think it's fine.","cultural_rating":5,"cultural_review":"The examples and exercises seem to be USA-centric (though I did spot one or two UK-based examples), but I do not think that it was being insensitive to any group.","overall_rating":10,"overall_review":"In addition to the above item-specific comments:\n\n#. I think that the first chapter has some good content about experiments vs. observational studies, and about sampling. Better than most of the introductory book that I have used thus far (granted, my books were more geared towards engineers).\n\n#. Some of the sections have only a few exercises, and more exercises are provided at the end of chapters. This is similar to many other textbooks, but since there are generally fewer section exercises, they are easy to miss when scrolling through, and provide less selection for instructors. I think it would be better to group all of the chapter's exercises until each section can have a greater number of exercises.\n\n#. I do not think that the exercises focus in on any discipline, nor do they exclude any discipline. This could be either a positive or a negative to individual instructors. I think in general it is a good choice, because it makes the book more accessible to a broad audience.\n\n#. That being said, I frequently teach a course geared toward engineering students and other math-heavy majors, so I'm not sure that this book would be fully suitable for my particular course in its present form (with expanded exercise selection, and expanded chapter 2, I would adopt it almost immediately).","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":791,"first_name":"Greg","last_name":"McAvoy","position":"Professor","institution_name":"University of North Carolina at Greensboro","comprehensiveness_rating":4,"comprehensiveness_review":"The book covers the essential topics in an introductory statistics course, including hypothesis testing, difference of means-tests, bi-variate regression, and multivariate regression. The authors make effective use of graphs both to illustrate the subject matter and to teach students how to construct and interpret graphs in their own work.  Examples from a variety of disciplines are used to illustrate the material.\n\nThe discussion of data analysis is appropriately pitched for use in introductory quantitative analysis courses in a variety of disciplines in the social sciences .  However, to meet the needs of this audience, the book should include more discussion of the measurement key concepts, construction of hypotheses, and research design (experiments and quasi-experiments).  These are essential components of quantitative analysis courses in the social sciences.\n\n\n","accuracy_rating":5,"accuracy_review":"The book covers familiar topics in statistics and quantitative analysis and the presentation of the material is accurate and effective.","relevance_rating":3,"relevance_review":"One of the real strengths of the book is the many examples and datasets that it includes.  Some of these will continue to be useful over time, but others may be may have a shorter shelf life.  In particular, examples and datasets about county characteristics, elections, census data, etc, can become outdated fairly quickly.","clarity_rating":4,"clarity_review":"Given that this is an introductory textbook, it is clearly written and accessible to students with a variety of disciplinary backgrounds.  The purpose of the course is to teach students technical material and the book is well-designed for achieving that goal.","consistency_rating":5,"consistency_review":" Like most statistics books, each topic builds on ones that have come before and readers will have no trouble following the terminology as they progress through the book.","modularity_rating":5,"modularity_review":"One of the real strengths of the book is that it is nicely separated into coherent chapters and instructors would will have no trouble picking and choosing among them.  For example, the authors have intentionally included a chapter on probability that some instructors may want to include, but others may choose to excludes without loss of continuity.\n","organization_rating":5,"organization_review":"The book does build from a good foundation in univariate statistics and graphical presentation to hypothesis testing and linear regression.  There are separate chapters on bi-variate and multiple regression and they work well together.  The chapter on hypothesis testing is very clear and effectively used in subsequent chapters.","interface_rating":5,"interface_review":"The formatting and interface are clear and effective.  There are lots of graphs in the book and they are very readable.  There are also pictures in the book and they appear clear and in the proper place in the chapters. ","grammatical_rating":5,"grammatical_review":"There are no issues with the grammar in the book.","cultural_rating":2,"cultural_review":"The authors present material from lots of different contexts and use multiple examples.  They have done an excellent job choosing ones that are likely to be of interest to and understandable by students with diverse backgrounds.","overall_rating":9,"overall_review":"The supplementary material for this book is excellent, particularly if instructors are familiar with R and Latex.  The code and datasets are available to reproduce materials from the book.  And, the authors have provided Latex code for slides so that instructors can customize the slides to meet their own needs. ","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":892,"first_name":"Gregg","last_name":"Stall","position":"Associate Professor","institution_name":"Nicholls State University","comprehensiveness_rating":5,"comprehensiveness_review":"The text covers the foundations of data, distributions, probability, regression principles and inferential principles with a very broad net. It is certainly a fitting means of introducing all of these concepts to fledgling research students. At the same time, the material is covered in such a matter as to provide future research practitioners with a means of understanding the possibilities when considering research that may prove to be of value in their respective fields.  In other words, breadth, yes; and depth, not so much.  It can be considered comprehensive if you consider this an introductory text. It's very fitting for my use with teachers whose primary focus is on data analysis rather than post-graduate research.  ","accuracy_rating":5,"accuracy_review":"The text is accurate due to its rather straight forward approach to presenting material.  In fact, I particularly like that the authors occasionally point out means by which data or statistics can be presented in a method that can distort the truth. Additionally concepts related to flawed practices in data collection and analysis were presented to point out how inaccuracies could arise in research. ","relevance_rating":4,"relevance_review":"While it would seem that the data in a statistics textbook would remain relevant forever, there are a few factors that may impact such a textbook's relevance and longevity.  Since this particular textbook relies heavily on the use of scenarios or case study type examples to introduce/teach concepts, the need to update this information on occasion is real.  These updates would serve to ensure the connection between the learner and the material that is conducive to learning. Additionally, as research and analytical methods evolve, then so will the need to cover more non-traditional types of content i.e mixed methodologies, non parametric data sets, new technological research tools etc.  ","clarity_rating":5,"clarity_review":"I feel that the greatest strength of this text is its clarity. The simple mention of the subject \"statistics\" can strike fear in the minds of many students. Perhaps we don't help the situation much with the way we begin launching statistical terminology while demonstrating a few \"concepts\" on a white board.  Well, this text provides a kinder and gentler introduction to data analysis and statistics.  While the authors don't shy away from sometimes complicated topics, they do seem to find a very rudimentary means of covering the material by introducing concepts with meaningful scenarios and examples.  ","consistency_rating":5,"consistency_review":"On occasion, all of us in academia have experienced a text where the progression from one chapter to another was not very seamless. This is especially true when there are multiple authors. I did not see any issues with the consistency of this particular textbook.  In fact, I could not differentiate a change in style or clarity in any sections of this text. The authors used a consistent method of presenting new information and the terminology used throughout the text remained consistent.  This is sometimes a problem in statistics as there are a variety of ways to express the similar statistical concepts. This can be particularly confusing to \"beginners.\" ","modularity_rating":5,"modularity_review":"While to some degree the text is easily and readily divisible into smaller reading sections, I would not recommend that anyone alter the sequence of the content until after Chapters 1, 3, and 4 are completed.  Materials in the later sections of the text are snaffled upon content covered in these initial chapters.  The authors point out that Chapter 2, which deals with probabilities, is  optional and not a prerequisite for grasping the content covered in the later chapters. Of course, the content in Chapters 5-8 would surely be useful  as supplementary materials/refreshers for students who have mastered the basics in previous statistical coursework. ","organization_rating":4,"organization_review":"After much searching, I particularly like the scope and sequence of this textbook.  As aforementioned, the authors gently introduce students to very basic statistical concepts.  These concepts are reinforced by authentic examples that allow students to connect to the material and see how it is applied in the real world. This introductory material then serves as the foundation for later chapter where students are introduced to inferential statistical practices.  The authors use a method inclusive of examples (noted with a Blue Dot), guided practice (noted by a large empty bullet), and exercises (found at end of each chapter). I find this method serves to give the students confidence in knowing that they understand concepts before moving on to new material.  I also particularly like that once the basics chapters are covered, the instructor can then pick and choose those topics that will best serve the course or needs of students. In some instances, various groups of students may be directed to certain chapters, while others hone in on that material relevant to their topic.","interface_rating":4,"interface_review":"I viewed the text as a PDF and was pleasantly surprised at the clarity the fluid navigation that is not the norm with many PDFs. The document was very legible.  The graphs and diagrams were also clear and provided information in a way that aided in understanding concepts.  This was not necessarily the case with some of the tables in the text.  I was sometimes confused by tables with missing data or, as was the case on page 11, when the table was sideways on the page. ","grammatical_rating":5,"grammatical_review":"I did not see any grammatical issues that distract form the content presented.","cultural_rating":5,"cultural_review":"I did not view an material that I felt would be offensive.  The material was culturally relevant to the demographic most likely to use the text in the United State. This is important since examples used authentic situations to connect to the readers.  While the examples did connect with the diversity within our country or i.e. the U.K., they may not be the best examples that could be used to connect with those from non-western countries. ","overall_rating":9,"overall_review":"The text would surely serve as an excellent supplement that will enhance the curriculum of any basic statistics or research course.  While the text could be used in both undergraduate and graduate courses, it is best suited for the social sciences. ","created_at":"2017-02-08T18:00:00.000-06:00","updated_at":"2017-02-08T18:00:00.000-06:00"},{"id":1467,"first_name":"Barbara","last_name":"Kraemer","position":"Part-time faculty","institution_name":"De Paul University School of Public Service","comprehensiveness_rating":4,"comprehensiveness_review":"The texts includes basic topics for an introductory course in descriptive and inferential statistics. The approach is mathematical with some applications.  More extensive coverage of contingency tables and bivariate measures of association would be helpful. Probability is an important topic that is included as a \"special topic\" in the course.","accuracy_rating":5,"accuracy_review":"The text and graphs are accurate.","relevance_rating":3,"relevance_review":"My interest in this text is for a graduate course in applied statistics in the field of public service.  This is a particular use of the text, and my students would benefit from and be interested in more social-political-economic examples. Some examples in the text are traditional ones that are overused, i.e., throwing dice and drawing cards to teach probability. The examples for tree diagrams are very good, e.g., small pox in Boston, breast cancer.","clarity_rating":4,"clarity_review":"The writing is clear, and numerous graphs and examples make concepts accessible to students. The text, however, is not engaging and can be dry.","consistency_rating":4,"consistency_review":"The text is consistent.","modularity_rating":5,"modularity_review":"The text is organized into sections, and the numbering system within each chapter facilitates assigning sections of a chapter. This is a statistics text, and much of the content would be kept in this order.","organization_rating":4,"organization_review":"The content is well-organized. The flow of a chapter is especially good when the authors continue to use a certain example in developing related concepts. There are exercises at the end of each chapter (and exercise solutions at the end of the text).","interface_rating":5,"interface_review":"Display of graphs and figures is good, as is the use of color. The graphs are readable in black and white also. The text is in PDF format; there are no problems of navigation.","grammatical_rating":5,"grammatical_review":"There are no grammatical errors.","cultural_rating":3,"cultural_review":"The examples are general and do not deal with racial or cultural matters.","overall_rating":8,"overall_review":"This text will be useful as a supplement in the graduate course in applied statistics for public service.","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":2382,"first_name":"Lily","last_name":"Huang","position":"Adjunct Math Instructor ","institution_name":"Bethel University","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers all the core topics of statistics—data, probability and statistical theories and tools. According to the authors, the text is to help students “forming a foundation of statistical thinking and methods,” unfortunately, some basic topics are missed for reaching the goal. For examples, the distinction between descriptive statistics and inferential statistics, the measures of central tendency and dispersion. These concepts should be clarified at the first chapter. ","accuracy_rating":4,"accuracy_review":"The text is mostly accurate but I feel the description of logistic regression is kind of foggy. The learner can’t capture what is logistic regression without a clear definition and explanation. It should be pointed out that logistic regression is using a logistic function to model a binary dependent variable. ","relevance_rating":4,"relevance_review":"The text needs real world data analysis examples from finance, business and economics which are more relevant to real life. As an example, I suggest the text provides data analysis by using Binomial option pricing model and Black-Scholes option pricing model. It should be appealing to the learners, dealing with a real-life case for better and deeper understanding of Binomial distribution, Normal approximation to the Binomial distribution. ","clarity_rating":4,"clarity_review":"The distinction and common ground between “standard deviation” and “standard error” needs to be clarified. ","consistency_rating":5,"consistency_review":"The contents are consistent.","modularity_rating":5,"modularity_review":"The modularity is creative and compares well. Chapter4 (foundations of inference), chapter 5 (inference of numerical data) and chapter 6 (inference of categorical data) provide clear and fresh logic for understanding statistics. ","organization_rating":5,"organization_review":"The organization/structure provides a smooth way for the contents to gradually progress in depth and breadth. ","interface_rating":5,"interface_review":"The interface is great! The nicely designed website (https://www.openintro.org) contains abundant resources which are very valuable for both students and teachers, including the labs, videos, forums and extras. This is the most innovative and comprehensive statistics learning website I have ever seen. ","grammatical_rating":5,"grammatical_review":"The grammar is good.","cultural_rating":5,"cultural_review":"The text is culturally inclusive with examples from diverse industries.","overall_rating":9,"overall_review":"There is a Chinese proverb: “one flaw cannot obscure the splendor of the jade.” In my opinion, the text is like jade, and can be used as a standalone text with abundant supplements on its website (https://www.openintro.org). It is especially well suited for social science undergraduate students. ","created_at":"2018-11-13T16:37:03.000-06:00","updated_at":"2018-11-13T16:37:03.000-06:00"},{"id":2655,"first_name":"Elizabeth","last_name":"Ward","position":"Assistant Professor ","institution_name":"James Madison University","comprehensiveness_rating":5,"comprehensiveness_review":"Covers all of the topics usually found in introductory statistics as well as some extra topics (notably: log transforming data, randomization tests, power calculation, multiple regression, logistic regression, and map data). Similar to most intro stat books, it does not cover the Bayesian view at all.   It does a more thorough job than most books of covering ideas about data, study design, summarizing data and displaying data. Online supplements cover interactions and bootstrap confidence intervals. \r\nThe book is written as though one will use tables to calculate, but there is an online supplement for TI-83 and TI-84 calculator. There are labs and instructions for using SAS and R as well.  \r\nThe index and table of contents are clear and useful. \r\n","accuracy_rating":5,"accuracy_review":"I have used this book now to teach for 4 semesters and have found no errors. It covers all the standard topics fully. ","relevance_rating":5,"relevance_review":"Many examples use real data sets that are on the larger side for intro stats (hundreds or thousands of observations). The book has relevant and easily understood scientific questions. It recognizes the prevalence of technology in statistics and covers reading output from software. Updates and supplements for new topics have been appearing regularly since I first saw the book (in 2013). In addition all of the source code to build the book is available so it can be easily modified. ","clarity_rating":5,"clarity_review":"The writing in this book is very clear and straightforward. It defines terms, explains without jargon, and doesn’t skip over details.  It has scientific examples for the topics so they are always in context.  I often assign reading and homework before I discuss topics in lecture. Students are able to follow the text on their own.  There are also matching videos for students who need a little more help to figure something out. ","consistency_rating":5,"consistency_review":"All of the notation and terms are standard for statistics and consistent throughout the book. ","modularity_rating":5,"modularity_review":"There are sections that can be added and removed at the instructor’s discretion. It would be feasible to use any part of the book without using previous sections as long as students had appropriate prerequisite knowledge. \r\nIn addition, some topics are marked as “special topics”. These are not necessary knowledge for future sections, so it is easy to see which sections you might leave out if there isn’t time or desire to complete the whole book. \r\n","organization_rating":5,"organization_review":"The topics all proceed in an orderly fashion. This book differs a bit in its treatment of inference. Ideas about “unusual” results are seeded throughout the early chapters. Then, the basics of both hypothesis tests and confidence intervals are covered in one chapter. The subsequent chapters have all of the specifics about carrying out hypothesis tests and calculating intervals for different types of data.\r\nI’ve grown to like this approach because once you understand how to do one Wald test, all the others are just a matter of using the same basic pattern using different statistics.   It definitely makes the students more comfortable with learning a new test because it’s “just the same thing” with different statistics.  \r\n","interface_rating":5,"interface_review":"Comes in pdf, tablet friendly pdf, and printed (15 dollars from amazon as of March, 2019). The pdf and tablet pdf have links to videos and slides. The text is easy to read without a lot of distracting clutter. \r\nThere are two drawbacks to the interface. The pdf is untagged which can make it difficult for students who are visually impaired and using screen readers. The second is that “examples” and “exercises” are numbered in a similar manner and students frequently confuse them early in the class. \r\n","grammatical_rating":5,"grammatical_review":"None. In addition, the book is written with paragraphs that make the text readable. (Unlike many modern books that seem to have random sentences scattered in between bullet points and boxes.)","cultural_rating":5,"cultural_review":"The  book includes examples from a variety of fields (psychology, biology, medicine, and economics to name a few). None of the examples seemed alarming or offensive. ","overall_rating":10,"overall_review":"There are many additional resources available for this book including lecture slides, a free online homework system, labs, sample exams, sample syllabuses, and objectives.  ","created_at":"2019-03-11T18:04:51.000-05:00","updated_at":"2019-03-11T18:04:51.000-05:00"},{"id":3528,"first_name":"Darin","last_name":"Brezeale","position":"Senior Lecturer","institution_name":"University of Texas at Arlington","comprehensiveness_rating":4,"comprehensiveness_review":"This book covers the standard topics for an introductory statistics courses: basic terminology, a one-chapter introduction to probability, a one-chapter introduction to distributions, inference for numerical and categorical data, and a one-chapter introduction to linear regression.  The overall length of the book is 436 pages, which is about half the length of some introductory statistics books.  Therefore, while the topics are largely the same the depth is lighter in this text than it is in some alternative introductory texts.","accuracy_rating":4,"accuracy_review":"Everything appeared to be accurate.  There were some author opinions on such things as how to go about analyzing the data and how to determine when a test was appropriate, but those things seem appropriate to me and are welcome in providing guidance to people trying to understand when to choose a particular statistical test or how to interpret the results of one.","relevance_rating":5,"relevance_review":"The material in the book is currently relevant and, given the topic, some of it will never be irrelevant.  The examples were up-to-date, for example, discussing the fact that Google conducts experiments in which different users are given search results in different ways to compare the effectiveness of the presentations.  Another welcome topic that is not typical of introductory texts is logistic regression, which I have seen many references to in the currently hot topic of Data Science.\r\n","clarity_rating":4,"clarity_review":"The text is well-written and with interesting examples, many of which used real data.","consistency_rating":4,"consistency_review":"The book was fairly consistent in its use of terminology.  The only issue I had in the layout was that at the end of many sections was a box high-lighting a term.  The issue I had with this was that I found the definitions within these boxes to often be more clear than when the term was introduced earlier, which often made me go looking for these boxes before I reached them naturally.","modularity_rating":4,"modularity_review":"The book is divided into many subsections.  I was able to read the entire book in about a month by knocking out a couple of subsections per day.\r\n","organization_rating":5,"organization_review":"The order of the topics seemed appropriate and not unlike many alternatives, but there was the issue of the term highlight boxes terms mentioned above.","interface_rating":5,"interface_review":"I read the physical book, which is easy to navigate through the many references.  In the PDF of the book, these references are links that take you to the appropriate section.","grammatical_rating":4,"grammatical_review":"I found virtually no issues in the grammar or sentence structure of the text.","cultural_rating":5,"cultural_review":"There aren't really any cultural references in the book.","overall_rating":9,"overall_review":"Overall, I liked the book.  The pros are that it's small enough that a person can work their way through it much faster than would be possible with many of the alternatives.  Within each chapter are many examples and what the authors call \"Guided Practice\"; all of these have answers in the book.  The odd-numbered exercises also have answers in the book.  I think that these features make the book well-suited to self-study.\r\n\r\nThe cons are that the depth is often very light, for example, it would be difficult to learn how to perform simple or multiple regression from this book.  Also, I had some issues finding terms in the index.","created_at":"2020-01-21T13:19:02.000-06:00","updated_at":"2020-01-21T13:19:02.000-06:00"},{"id":3698,"first_name":"Alice","last_name":"Brawley Newlin","position":"Assistant Professor","institution_name":"Gettysburg College","comprehensiveness_rating":4,"comprehensiveness_review":"I found the book to be very comprehensive for an undergraduate introduction to statistics - I would likely skip several of the more advanced sections (a few of these I mention below in my comments on its relevance) for this level, but I was glad to see them included. I also found it very refreshing to see a wide variability of fields and topics represented in the practice problems.\r\n\r\nOne topic I was surprised to see trimmed and placed online as extra content were the calculations for variance estimates in ANOVA, but these are of course available as supplements for the book. Two topics I found absent were the calculation of effect sizes, such as Cohen's d, and the coverage of interval and ratio scales of measurement (the authors provide a breakdown of numerical variables as only discrete and continuous). I did have a bit of trouble looking up topics in the index - the page numbers seemed to be off for some topics (e.g., effect size).","accuracy_rating":5,"accuracy_review":"I did not see any issues with accuracy, though I think the p-value definition could be simplified.","relevance_rating":5,"relevance_review":"I found the content in the 4th edition is extremely up-to-date - both in terms of its examples, and in terms of keeping up with the \"movements\" in many disciplines to be more transparent and considered in hypothesis testing choices (e.g., all hypothesis tests are two-tailed [though the reasoning for this is explained, especially in Section 5.3.7 on one-tailed tests), they include Bayes' theorem, many less common distributions for the introductory level like Bernoulli and Poisson, and estimating statistical power/desired sample size). The sections on these advanced topics would make this a candidate for more advanced-level courses than the introductory undergraduate one I teach, and I think will help with longevity. The examples will likely become dated, but that is always the case with statistics textbooks; for now, they all seem very current (in one example, we solve for the % of cat videos out of all the videos on Youtube).","clarity_rating":5,"clarity_review":"I found the book's prose to be very straightforward and clear overall. The p-value definition could be simplified by eliminating mention of a hypothesis being tested.","consistency_rating":5,"consistency_review":"I did not find any issues with consistency in the text, though it would be nice to have an additional decimal place reported for the t-values in the t-table, so as to make the presentation of corresponding values between the z and t-tables easier to introduce to students (e.g., tail p of .05 corresponds to t of 1.65 - with rounding - in large samples; but the same tail p falls precisely halfway between z of 1.64 and z of 1.65).","modularity_rating":5,"modularity_review":"The sections seem easily labeled and would make it easy to skip particular sections, etc. The authors also offer an \"alternative\" series of sections that could be covered in class to fast-track to regression (the book deals with grouped analyses first) in their introduction to the book.","organization_rating":5,"organization_review":"I found the overall structure to be standard of an introductory statistics course, with the exception of introducing inference with proportions first (as opposed to introducing this with means first instead). However, even with this change, I found the presentation to overall be clear and logical.","interface_rating":4,"interface_review":"The B\u0026W textbook did not seem to pose any problems for me in terms of distortion, understanding images/charts, etc., in print. However, I did find the inclusion of practice problems at the end of each section vs. all together the end of the whole chapter (which is the new arrangement in the 4th edition) to be a challenge - specifically, this made it difficult for me to identify easily where sections ended, and in some places, to follow the train of thought across sections. This could make it easier for students or instructors alike to identify practice on particular concepts, but it may make it more difficult for students to grasp the larger picture from the text alone.","grammatical_rating":5,"grammatical_review":"I did not find any grammatical errors.","cultural_rating":5,"cultural_review":"I was impressed by the scope of fields represented in the example problems - everything from estimating the length of possums' heads, to smoke inhalation in one's line of work, to child development, and so on.","overall_rating":10,"overall_review":"I reviewed a paperback B\u0026W copy of the 4th edition of this book (published 2019), which came with a list describing the major changes/reorganization that was done between this and the 3rd edition.","created_at":"2020-03-31T17:27:05.000-05:00","updated_at":"2020-03-31T17:27:05.000-05:00"},{"id":4334,"first_name":"Kendall","last_name":"Rosales","position":"Instructor and Service Level Coordinator","institution_name":"Western Oregon University","comprehensiveness_rating":4,"comprehensiveness_review":"There is more than enough material for any introductory statistics course.  There are a lot of topics covered.  The topics are not covered in great depth; however, as an introductory text, it is appropriate.    My biggest complaint is that one-sided tests are basically ignored.  There is only a small section explaining why they do not use one sided tests and a brief explanation on how to perform a one sided test.","accuracy_rating":4,"accuracy_review":"It is accurate.  There is also a list of known errors that shows that errors are fixed in a timely manner.  There is some bias in terms of what the authors prioritize. I am not necessarily in disagreement with the authors, but there is a clear voice.","relevance_rating":4,"relevance_review":"For the most part, examples are limited to biological/medical studies or experiments, so they will last.  There are a few instances referencing specific technology (such as iPods) that makes the text feel a bit dated.","clarity_rating":5,"clarity_review":"The narrative of the text is grounded in examples which I appreciate.  The authors introduce a definition or concept by first introducing an example and then reference back to that example to show how that object arises in practice.","consistency_rating":5,"consistency_review":"The terms and notation are consistent throughout the text.","modularity_rating":5,"modularity_review":"Each chapter is broken up into sections and each section has sub-sections using standard LaTex numbering.  There are chapters and sections that are optional.  So future sections will not rely on them.  In particular, I like that the probability chapter (which comes early in the text) is not necessary for the chapters on inference.","organization_rating":4,"organization_review":"The topics are in a reasonable order.  An interesting note is that they introduce inference with proportions before inference with means.","interface_rating":5,"interface_review":"No display issues with the devices that I have.","grammatical_rating":5,"grammatical_review":"Typos that are identified and reported appear to be fixed within a few days which is great.","cultural_rating":4,"cultural_review":"Examples stay away from cultural topics.  However, there are a few instances where he/she are used to refer to a \"theoretical person\" rather than using they/them","overall_rating":9,"overall_review":null,"created_at":"2020-08-20T11:51:40.000-05:00","updated_at":"2020-08-20T11:51:40.000-05:00"},{"id":4582,"first_name":"Monte","last_name":"Cheney","position":"Associate Professor","institution_name":"Central Oregon Community College","comprehensiveness_rating":2,"comprehensiveness_review":"Unless I missed something, the following topics do not seem to be covered: stem-and-leaf plots, outlier analysis, methods for finding percentiles, quartiles, Coefficient of Variation, inclusion of calculator or other software, combinatorics, simulation methods, bootstrap intervals, or CI's for variance, critical value method for testing, and nonparametric methods.","accuracy_rating":5,"accuracy_review":"No inaccuracies found.","relevance_rating":4,"relevance_review":"Statistics is not a subject that becomes out of date, but in the last couple decades, more emphasis has been given to usage of computer technology and relevant data. Lots of good graphics and referenced data sets, but not much discussion or inclusion of prevailing software such as R, SPSS, Minitab, or free online packages.","clarity_rating":4,"clarity_review":"Some topics in descriptive statistics are presented without much explanation, such as dotplots and boxplots. Also, the discussion on hypothesis testing could be more detailed and specific.","consistency_rating":5,"consistency_review":"No issues noted.","modularity_rating":5,"modularity_review":"Seems fine.","organization_rating":3,"organization_review":"The rationale for assigning topics in Section 1 and 2 is not clear. Also, grouping confidence intervals and hypothesis testing in Ch.5 is odd, when Ch.7 covers hypothesis testing of numerical data. And why dump Ch.6 in between with hypothesis testing of categorical data between them?","interface_rating":5,"interface_review":"Interface appears to be seamless.","grammatical_rating":5,"grammatical_review":"No problems noted.","cultural_rating":5,"cultural_review":"No cultural insensitivity noted.","overall_rating":9,"overall_review":"Overall, I would consider this a decent text for a one-quarter or one-semester introductory statistics textbook. The presentation is professional with plenty of good homework sets and relevant data sets and examples. However, it would not suffice for our two-quarter statistics sequence that includes nonparametrics. The lack of discussion/examples/inclusion of statistical software or calculator usage is disappointing, as is the inclusion of statistical inference using critical values. The fourth edition is a definite improvement over previous editions, but still not the best choice for our curriculum.","created_at":"2021-01-15T14:00:51.000-06:00","updated_at":"2021-01-15T14:00:51.000-06:00"},{"id":4807,"first_name":"Denise","last_name":"Wilkinson","position":"Professor of Mathematics","institution_name":"Virginia Wesleyan University","comprehensiveness_rating":5,"comprehensiveness_review":"This text book covers most topics that fit well with an introduction statistics course and in a manageable format. The chapter summaries are easy to follow and the order of the chapters begin with \"Introduction to Data,\" which includes treatment and control groups, data tables and experiments. The final chapters, \"Introduction to regression analysis\" and \"Multiple and logistical regression\"  fit nicely at the end of the text book. This may allow the reader to process statistical terminology and procedures prior to learning about regression.  The text book contains a detailed table of contents, odd answers in the back and an index.","accuracy_rating":5,"accuracy_review":"I have not noted any inconsistencies, inaccuracies, or biases.","relevance_rating":5,"relevance_review":"The examples are up-to-date, but general enough to be relevant in years to come or formatted appropriately so that, if necessary, they may be easily replaced.","clarity_rating":5,"clarity_review":"This book is very readable. Each chapter begins with a summary and a URL link to resources like videos, slides, etc. The definitions are clear and easy to follow. The examples and solutions represent the information with formulas and clear process. The examples flow nicely into the guided practice problems and back to another example, definition, set of procedural steps, or explanation. Each section ends with a problem set. Students can check their answers to the odd questions in the back of the book.","consistency_rating":5,"consistency_review":"The format  is consistent throughout the textbook. The definitions and procedures  are clear and presented in a framework that is easy to follow. The bookmarks of chapters are easy to locate. The reader can jump to each chapter, exercise solutions, data sets within the text, and distribution tables very easily.","modularity_rating":5,"modularity_review":"The chapters are bookmarked along the side of the pdf file (once downloaded). Each chapter is separated into sections and subsections. Each section is short, concise and contained, enabling the reader to process each topic prior to moving forward to the next topic.","organization_rating":5,"organization_review":"The organization of the topics is unique, but logical. The first chapter addresses treatments, control groups, data tables and experiments. This topic is usually covered in the middle of a textbook. This is a good position to set up the thought process of students to think about how statisticians collect data.","interface_rating":4,"interface_review":"The colors of the font and tables in the textbook are mostly black and white. There are a few color splashes of blue and red in diagrams or URL's. At first when reviewing, I found it to be difficult for to quickly locate definitions and examples and often focus on the material. I was concerned that it also might add to the difficulty of analyzing tables. However, after reviewing the textbook at length, I did note that it did become easier to follow the text with the omission of colorful fonts and colors, which may also  be noted as distraction for some readers. \r\nI do like the case studies, videos, and slides. I believe students, as well as, instructors would find these additions helpful. The Guided Practice problems allow students to try a problem with the solution in the footnote at the bottom. These blend well with the Exercises that contain the odd solutions at the end of the text.","grammatical_rating":5,"grammatical_review":"There do not appear to be grammatical errors.","cultural_rating":5,"cultural_review":"There are a variety of exercises that do not represent insensitivity or offensive to the reader. There are a variety of interesting topics in the exercises that include research on the relationship between honesty, age and self control with children; an experiment on a treatment for asthma patients; smoking habits in the U.K.; a study on migraines and acupuncture; and a study on sinusitis and antibiotics.","overall_rating":10,"overall_review":"I value the unique organization of chapters, the format of the material, and the resources for instructors and students. The textbook offers companion data sets on their website, and labs based on the free software, R and Rstudio. There are also short videos for 75% of the book sections that are easy to follow and a plus for students.","created_at":"2021-04-20T16:24:05.000-05:00","updated_at":"2021-04-20T16:24:05.000-05:00"},{"id":5092,"first_name":"Leanne","last_name":"Merrill","position":"Assistant Professor","institution_name":"Western Oregon University","comprehensiveness_rating":5,"comprehensiveness_review":"This book has both the standard selection of topics from an introductory statistics course along with several in-depth case studies and some extended topics. In particular, the malaria case study and stokes case study add depth and real-world meaning to the topics covered, and there is a thorough coverage of distributions. If you are looking for deep mathematical comprehensiveness of exercises, this may not be the right book, but for most introductory statistics students who are not pursuing deeper options in math/stat, this is very comprehensive.","accuracy_rating":5,"accuracy_review":"I see essentially no errors in this book. The book appears professionally copy-edited and easy to read. I do not detect a bias in the work.","relevance_rating":5,"relevance_review":"I find the content to be quite relevant. Almost every worked example and possible homework exercise in the book is couched in real-world situation, nearly all of which are culturally, politically, and socially relevant. I do think there are some references that may become obsolete or lost somewhat quickly; however, I think a diligent editorial team could easily update data sets and questions to stay current.","clarity_rating":4,"clarity_review":"The writing in this book is above average. However, there are some sections that are quite dense and difficult to follow. The writing could be slightly more inviting, and concept could be more readily introduced via accessible examples more often. Words like \"clearly\" appear more than are warranted (ie: ever). As a mathematician, I find this book most readable, but I imagine that undergraduates might become somewhat confused. Jargon is introduced adequately, though.","consistency_rating":5,"consistency_review":"The book reads cleanly throughout. Nothing was jarring in this aspect, and the sections/chapters were consistent.","modularity_rating":5,"modularity_review":"This book is highly modular. I teach at an institution with 10-week terms and I found it relatively easy to subdivide the material in this book into a digestible 10 weeks (I am not covering the entire book!). Many OERs (and published textbooks) are difficult to convert from a typical 15-week semester to a 10-week term, but not this one! This book is easy to follow and the roadmap at the front for the instructor adds additional ease.","organization_rating":4,"organization_review":"This book is very clearly laid out for both students and faculty. The student-facind end, while not flashy or gamified in any way, is easy to navigate and clear. The primary ways to navigate appear to be via the pdf and using the physical book. It would be nice to have an e-book version (though maybe I missed how to access this on the website). For faculty, everything is very easy to find on the OpenIntro website.","interface_rating":3,"interface_review":"I found no problems with the book itself. I do wonder about accessibility (for blind or deaf/HoH students) in this book since I don't see it clearly addressed on the website. The pdf is likely accessible for screen readers, though. I do think a more easily navigable e-book would be ideal.","grammatical_rating":5,"grammatical_review":"I did not find any grammatical errors that impeded meaning. There is an up-to-date errata maintained on the website.","cultural_rating":4,"cultural_review":"This book does not contain anything culturally insensitive, certainly. However, I think a greater effort could be made to include more culturally relevant examples in this book. It appears to stick to more non-controversial examples, which is perhaps more effective for the subject matter for many populations.","overall_rating":9,"overall_review":"This book is quite good and is ethically produced.","created_at":"2021-06-14T03:44:05.000-05:00","updated_at":"2021-06-14T03:44:05.000-05:00"},{"id":33854,"first_name":" Hamdy","last_name":"Mahmoud","position":"Collegiate Assistant Professor","institution_name":"Virginia Tech","comprehensiveness_rating":5,"comprehensiveness_review":"This book covers almost all the topics needed for an introductory statistics course from introduction to data to multiple and logistic regression models. One of the good topics is the random sampling methods, such as simple sample, stratified, cluster, and multistage random sampling methods. Also, the convenient sample is covered. If the volunteer sample is covered also that would be great because it is very common nowadays. The chapters are well organized and many real data sets are analyzed.","accuracy_rating":5,"accuracy_review":"I use this book in teaching and I did not find any issues with accuracy, inconsistency, or biasness.","relevance_rating":5,"relevance_review":"I find the content quite relevant. The real data sets examples cover different topics, such as politics, medicine, … etc. The examples are up-to-date. The resources, such as labs, lecture notes, and videos are good resources for instructors and students as well. Labs are available in many modern software: R, Stata, SAS, and others. Although it covers almost all the basic topics for an introductory course, it has some advanced topics which make it a candidate for more advanced courses as well and I believe this will help with longevity.","clarity_rating":5,"clarity_review":"Overall, the text is well-written and explained along with real-world data examples. In addition, it is easy to follow. Each chapter starts with a very interesting paragraph or introduction that explains the idea of the chapter and what will be covered and why.","consistency_rating":5,"consistency_review":"No issues with consistency in that text are found. The statistical terms, definitions, and equation notations are consistent throughout the text.","modularity_rating":5,"modularity_review":"The way the chapters are broken up into sections and the sections are broken up into subsections makes it easy to select the topics that need to be covered in a course based on the number of weeks of the course. It is easy to skip some topics with no lack of consistency or confusion.","organization_rating":5,"organization_review":"The book is well organized and structured. Having a free pdf version and a hard copy for a few dollars is great. The resources on the website also are well organized and easy to access and download. Choosing the population proportion rather than the population mean to be covered in the foundation for inference chapter is a good idea because it is easier for students to understand compared to the population mean.","interface_rating":4,"interface_review":"The interface of the book appears to be fine for me, but more attractive colors would make it better.","grammatical_rating":5,"grammatical_review":"I did not find any grammatical errors or typos.","cultural_rating":5,"cultural_review":"I did not notice any culturally sensitive examples, and no controversial or offensive examples for the reader are presented.","overall_rating":10,"overall_review":"Overall, I recommend this book for an introductory statistics course, however, it has some advanced topics.","created_at":"2022-05-16T22:51:35.000-05:00","updated_at":"2022-05-16T22:51:35.000-05:00"},{"id":34669,"first_name":"Sanduni","last_name":"Palliyage","position":"Lecturer","institution_name":"James Madison University","comprehensiveness_rating":4,"comprehensiveness_review":"This book includes introduction to data, summarizing data (numerical and graphical), probability, distributions of random variables, inference for categorical and numeric data, linear regression, multiple linear regression and logistic regression. This covers almost all the topics that should cover in an introductory statistics course. I could not find counting techniques in this book.","accuracy_rating":5,"accuracy_review":"I did not find any accuracy issues in this book.","relevance_rating":5,"relevance_review":"This book contains basic concepts in statistics. These concepts will not change within a short period of time. Questions/examples in this book cover a wide range of area. Examples and questions can be update as time changes. I do not think this book needs any major changes recently.","clarity_rating":4,"clarity_review":"Overall clarity of this book is admirable. Topic lineup and teaching methods are different from person to person. There were some sections I would love to see a better explanation or more examples. For example, inference is something that students struggle a lot. I would like to see a better explanation on hypothesis test before we move on to hypothesis testing on proportions or means.","consistency_rating":5,"consistency_review":"I did not find any consistency issues in this book.","modularity_rating":5,"modularity_review":"In this book, I noticed the sections and the sub sections are concise and clear.","organization_rating":5,"organization_review":"I like the structure of this book and the chapters are organized well. Because of this logical flow of the chapters, it is very easy to follow this book.","interface_rating":5,"interface_review":"I did not have any interface issues, navigation problems or any features that distract or confuse me.","grammatical_rating":5,"grammatical_review":"I didn't find any grammatical errors.","cultural_rating":5,"cultural_review":"I did not find this book culturally insensitive or offensive.","overall_rating":10,"overall_review":"OpenIntro Statistic is a very good book for introductory statistics classes.","created_at":"2023-09-05T14:49:03.000-05:00","updated_at":"2023-09-05T14:49:03.000-05:00"},{"id":35071,"first_name":"Njesa","last_name":"Totty","position":"Assistant Professor of Statistics","institution_name":"Framingham State University","comprehensiveness_rating":5,"comprehensiveness_review":"The book does cover data collection and visualization, random variables, distributions, and inference up through logistic regression. This is great for an introductory statistics course.","accuracy_rating":5,"accuracy_review":"The content of the textbook is highly accurate.","relevance_rating":5,"relevance_review":"The content is relevant and examples are quite useful.","clarity_rating":5,"clarity_review":"The book does a great job explaining otherwise confusing topics for the introductory statistics student.","consistency_rating":5,"consistency_review":"The book's consistency is great. I have been using it for years and the organization and framework are really well structured.","modularity_rating":5,"modularity_review":"The modularity of the textbook is quite great.","organization_rating":5,"organization_review":"The book is well organized and flows well through a reasonable sequence of topics to get student introduced to statistics.","interface_rating":5,"interface_review":"The interface of the textbook is great. I appreciate the inclusion of exercise solutions and many examples.","grammatical_rating":5,"grammatical_review":"There are no grammatical errors in this textbook that I know of.","cultural_rating":5,"cultural_review":"This textbook is culturally sensitive.","overall_rating":10,"overall_review":"Great textbook with lots of other resources!","created_at":"2024-05-24T15:29:15.000-05:00","updated_at":"2024-05-24T15:29:15.000-05:00"},{"id":35428,"first_name":"Chris","last_name":"Price","position":"Assistant Professor","institution_name":"James Madison University","comprehensiveness_rating":4,"comprehensiveness_review":"I think this is a good text-book for getting students to understand key parts of statistics, notably understanding sampling, summary statistics, the role of probability, and hypothesis testing. Unlike previous open access works by at least one of these authors, there are no chapter ending summaries/cheat sheets, something which I believe students find helpful. \n  The ending chapter moves very quickly through Logit regression and the idea of Generalized Linear models. I thought this could be expanded to be more effective, but I realize this may not work in shorter courses on statistics or be something that instructors would approach in a second semester focused on regression. \n  One big issue I would see in using this is that I think there needs to be more on the R statistics application. The authors provide a lot of valuable data for examples, as well as discussing the importance of R in using these, but there's not much guidance for a student on how to do this in the textbook. \n  Lastly, I like the idea of moving some of the more esoteric topics to online appendices, I think these could either be moved to the end of the chapters. I also worry whether these online supplements will be out there in the future.","accuracy_rating":5,"accuracy_review":"In going through, I didn't find any glaring errors, although there are some places (for example, their description of Bayes' rule, or standard errors) where I think they could improve the order of explanation, particularly in clarifying the mathematical terms for students. \n  I only did a few examples, but I did not find any errors in the examples, guided learning, or chapter exercises. Especially given the number of examples and guided practice problems, I thought this was an achievement, and that these descriptions would help a student working on their own to improve their confidence on these concepts.\n   There are some parts where there are inconsistencies in the formatting of white space, and the authors note that the pagination in the pdf is not the same as in the print version.","relevance_rating":5,"relevance_review":"I thought the book was well set up for the future, and that the graphics and software used, which are open source, should be long lasting. I know from using Cetinkaya-Rundel and Hardin's Open Introduction to Modern Statistics, it's clear that they've been able to update these chapters easily enough.  I also didn't observe any easily dated examples, and most of these topics aren't likely to change anytime soon.","clarity_rating":4,"clarity_review":"I think the authors do a good job in providing definitions in easy-to-understand terms and providing clear signposts to students of what's important as they go through each section/chapter.  I think adding more on mathematical notation in some of the earlier chapters (For example, 2.3.0 seems to use notation not introduced by that point), perhaps as end of chapter or section notes, would help with this. \n  There are some sections which could be clearer, but I think as an instructor I'd easily be able to explain in more detail in class. For example, Bayes Rule (sec 3.2/P119) uses a correct, but more complex equation than I would normally show. The discussion of robustness in 2.1.6 is one where I think students would not necessarily understand this point, but an instructor would easily.","consistency_rating":5,"consistency_review":"I did not observe any major inconsistencies in the terminology and framework. I think that in Chapter 6, there are times where an introductory student would not follow the concept of standard error when first introduced, but this is only point which really struck me. While there are different approaches to organizing and teaching statistics, I thought the organization was more effective for my class than some of the other competing textbooks, which often push probability to the end of the text or put computer coding earlier. \n   I think there are some inconsistencies in the way that they flag key terms or equations (for example, comparing the box/equation for sample mean on P47 vs Standard Deviation/Variance on P54), but I did not find any key terms which didn't have some kind of bolding/text signal to alert students to key terms.","modularity_rating":5,"modularity_review":"This is easily cut into modules, and I would see myself omitting some of the modules. It's also important to note that the authors point out that the page numbers in the pdf and print version are different, so as an instructor you'd need to specify modules rather than pages. \n   There are some places where I'd definitely separate or skip certain modules. For example, module 2.3.0 seems to me to work much better later in the organization of the course/text book, and I would separate sections 3.4 - 3.5, discussing random variables, to chapter 4 with the discussion of distributions.","organization_rating":5,"organization_review":"The organization makes sense, and I believe that the authors have done a better job of organizing topics than some of the other competing textbooks, Cetnikaya-Rundel and Hardin or Llaudet and Imai, in matching how I think it's effective to explain these topics to students. \n\nIn the modules, I think they could improve by adding glossary/cheat sheets at the end of the chapter.  I also think there are some points where they could improve the organization of examples/guided practice, for example P50/51, 59/60. My sense is that they're using a sandwich - student try it themselves, show example, then a harder student does it themselves - but this flips sometimes in the individual chapters.","interface_rating":5,"interface_review":"There are some small issues where figures fall into the next section or there's odd white spaces (for example, P217/218, 247/248, 51/52), but otherwise, I didn't recognize major issues in the interface. In fact, I think that the figures and equations are quite clearly formatted, and can definitely see these working well for a student even if they were using a phone or tablet. \n   I know from the website, the pagination is different between pdf/print, so would stick with module number rather than page numbers.","grammatical_rating":5,"grammatical_review":"The book is well copy-edited - I found one typo in the reading, but otherwise the text has clearly been edited, and I think is accessible to an undergraduate taking statistics.","cultural_rating":5,"cultural_review":"I thought the authors went to lengths to try and make sure language was inclusive, that there were examples from across different disciplines, and that where contentious topics were addressed, the focus was on how statistics can help us find common ground. The only thing I found which I thought would be problematic was on P275, where they discuss human's eating dolphin meat.","overall_rating":10,"overall_review":"I think this would be a good choice for addressing principles of probability and statistics in a social science methods course. As an instructor, it divides well into separate parts, and they are written in a way which will be accessible without a student having read the entire text. However, you would likely still need to design your course to include more background on R for students, to help them get the most out of the guided practice or chapter exercises.","created_at":"2025-03-29T23:45:27.000-05:00","updated_at":"2025-03-29T23:45:27.000-05:00"},{"id":35555,"first_name":"Jennifer","last_name":"Bowen","position":"Professor and Dean","institution_name":"The College of Wooster","comprehensiveness_rating":5,"comprehensiveness_review":"This is an excellent text to use for students in an undergraduate Intro to Statistics course. Students can cover nearly all the topics in in the Table of Contents. The set of associated labs in R are skillfully designed for all students, no matter what their backgrounds. The labs overlay with the text content seamlessly and offer hands on experience with R and provided datasets. The terminology throughout the text is clearly defined for students, set at the right level for an introductory course, and the text provides profuse examples.","accuracy_rating":5,"accuracy_review":"In my experience teaching with this textbook, the accuracy is not a worry. Student information is delivered without error and the text is readable without bias. I had no experience with errors that were detrimental to teaching or student learning - which has been common with other intro statistics books I've taught from in the past.","relevance_rating":5,"relevance_review":"This text is up-to-date, artfully incorporating introductory material in labs and within the text from statistical packages, including basic R commands and programming. Updates will be very easy and straightforward to implement for students. The text makes the instructor's job easy to convey the material to students. I am grateful to the authors for including real datasets, with real R commands and instructions to students. The R experiences in this text are resume-level power skills for an introductory student.","clarity_rating":5,"clarity_review":"OpenIntro Statistics is a great text for students to be able to read along easily, terminology is defined quickly and accurately, and in an unassuming way.","consistency_rating":5,"consistency_review":"This text is consistent with terminology and framework - both students and instructor know what to expect from chapters and sections throughout the book. The framework is easy to follow, the examples are comprehensive and student-friendly.","modularity_rating":5,"modularity_review":"OpenIntro Statistics is a a terrific textbook to subdivide into small reading assignments for students, either outside or inside of class.","organization_rating":5,"organization_review":"This text is organized in a thoughtful way, building upon material as a student works through the book.","interface_rating":5,"interface_review":"The text is totally free of significant interface issues that impede any readability and understanding. The navigation is professional and easy to access and follow. There is no distortion of images, charts, or displays of information.","grammatical_rating":5,"grammatical_review":"I have found no grammatical errors in my experience with this textbook -- this is something that I truly noticed, as it has been a problem with other introductory texts that I have used and reviewed.","cultural_rating":5,"cultural_review":"This text is culturally sensitive -- this is an important quality to me as a faculty member at a small liberal arts institution.","overall_rating":10,"overall_review":null,"created_at":"2025-06-27T15:31:59.000-05:00","updated_at":"2025-06-27T15:31:59.000-05:00"},{"id":35694,"first_name":"Keuntae","last_name":"Kim","position":"Assistant Professor","institution_name":"Old Dominion University","comprehensiveness_rating":4,"comprehensiveness_review":"I purchased the third edition of this book. I am particularly impressed with its comprehensiveness because this book covers the breadth of topics on introductory statistics, ranging from data basics to advanced regression models. Also, on the separate OpenIntro website, the authors have continuously updated the book's content and corrected errata, making it more comprehensive and distinguishable from other introductory statistics books that remain static for a while after publication. This dedication ensures that the material remains not only complete but also practically robust, filling gaps. For teaching purposes, this textbook is also very suitable for teaching introductory statistical techniques to students in one semester.\r\nPersonally, I have one suggestion for the future edition: Given how recent trends in data analytics have shifted, I would love to see brief introductory content on Big Data, Machine Learning, and AI in the next major edition (i.e., the fifth edition). These topics are becoming central and critical to both academic research and professional practice. While this is an introductory stats book, adding a primer on these modern tools would help students connect the dots between classical statistics and the rapidly evolving world of data science.","accuracy_rating":5,"accuracy_review":"Through continuous updates, the content of this book is now highly polished and very accurate, which is another strength of this book. The mathematical formulas and statistical concepts are clearly and accurately explained throughout this book, making them accessible and easy to understand for readers with a variety of datasets and examples. While using this book for my self-study and as a reference for my statistics class, I have not encountered any errors or biases, which makes this book reliable and valid. The clear explanations of concepts and formulas help students grasp key ideas effectively. Therefore, I would say this book would be a strong choice for an Introductory Statistics course as an instructor.","relevance_rating":4,"relevance_review":"Using real-world datasets (e.g., medical studies, financial trends) and examples makes this book remain relevant and engaging. The content is structured modularly, and since the source files are hosted on GitHub, implementing necessary updates is technically straightforward and transparent. One thing I would like to suggest is regarding the \"up-to-date\" criterion. It has been six years since the 4th Edition was released in 2019. Given the rapidly evolving field of data analysis, it would be a great time to consider another major update to this book. While the core traditional descriptive and inferential statistical concepts remain solid and the text is not yet obsolete, I believe a comprehensive '5th Edition' update is now necessary to ensure the content uses and reflects the datasets and examples after 2020.","clarity_rating":5,"clarity_review":"The writing style and language in this book are in plain English, making the content very easy to understand and suitable for students to conduct their own self-study to develop their statistical analysis skills. Also, the mathematical formulas and concepts are well explained with real-world, practical examples. It reads less like a dense instruction manual and more like a guided conversation, which is another nice thing about this book as a textbook for Introductory Statistics.","consistency_rating":5,"consistency_review":"The table of contents in this book shows a well-organized and predictable structure, which helps students settle into the book. Features like the 'Guided Practice' boxes appear regularly with solutions always located in the footnotes, creating a steady feedback loop. The visual language is also cohesive, with graphs and tables sharing a unified design aesthetic (clean, R-style plots) across all sections.","modularity_rating":5,"modularity_review":"As the authors mentioned in the Preface, each chapter functions as an independent module, allowing instructors to design flexible teaching pathways tailored to their courses. This modular structure also enables students to engage with statistical techniques according to their interests and study pace. The OpenIntro website further supports this flexibility by offering guidance for both course-based use and self-study. The text minimizes unnecessary cross-referencing to nonessential sections, making it remarkably easy to rearrange units to fit a customized syllabus without confusing readers.","organization_rating":5,"organization_review":"The organization of chapters and the flow of the text are highly logical and reflect the typical workflow of a data analyst. For instance, the transition from probability (Chapter 3) to inference (Chapter 5) is effectively supported by the intervening chapter on distributions (Chapter 4), which helps prevent students from becoming overwhelmed or disoriented. The overall progression is natural and cumulative, guiding readers smoothly toward more advanced topics such as regression.","interface_rating":4,"interface_review":"The PDF version of the book is well-designed and polished, and there are no issues navigating the text, exercises, graphs, or tables. However, I rated this aspect a 3 out of 5 because of a major usability limitation in how the computing components are handled. Ideally, I want students to learn theory and coding (whether in R or Python) together within the same textbook. In this case, though, all of the coding labs are separated from the main text, requiring students to move back and forth between the PDF and the OpenIntro website to access the R or Python examples. For future editions, I hope the authors will integrate the theory and coding practices into a single, unified PDF so that students can learn both components more seamlessly.","grammatical_rating":5,"grammatical_review":"So far, I haven't identified any grammatical and expression errors in the textbook. Its continuous updates and quick responses to feedback minimize grammatical errors in the text, which is another strength that enhances the reliability and validity of this book.","cultural_rating":5,"cultural_review":"I did not see any cultural biases or racial prejudices in the textbook. The datasets and real-world examples it uses are broadly applicable, globally relevant, and grounded in sound scientific practice. As a social scientist, I hope to see more examples from the social sciences that use demographic and socioeconomic data, but the current edition of the textbook prioritizes datasets across various themes, such as health, medicine, economics, housing, etc. Looking at examples and exercises in the book, I can say that the content is professional, objective, and free of any culturally insensitive language or bias.","overall_rating":9,"overall_review":"OpenIntro Statistics is an excellent “study bible” for both students and instructors. It provides a strong, reliable foundation in statistics, explained in clear, accessible language. The mathematical formulas and concepts are easy to follow, supported by numerous examples and exercises. I look forward to seeing and buying (if necessary) the next major edition and hope it will address some of the gaps I noted in my review. By making such high-quality materials freely available, the authors are genuinely helping to reduce financial barriers for students around the world.","created_at":"2025-12-11T13:21:08.000-06:00","updated_at":"2025-12-11T13:21:08.000-06:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/openintro-statistics","updated_at":"2026-06-25T09:08:59.000-05:00"},{"id":95,"title":"Basic Analysis: Introduction to Real Analysis","edition_statement":null,"volume":null,"copyright_year":2016,"isbn10":null,"isbn13":null,"license":"Attribution-NonCommercial-ShareAlike","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"This free online textbook (e-book in webspeak) is a one semester course in basic analysis. This book started its life as my lecture notes for Math 444 at the University of Illinois at Urbana-Champaign (UIUC) in the fall semester of 2009, and was later enhanced to teach Math 521 at University of Wisconsin-Madison (UW-Madison). A prerequisite for the course is a basic proof course. It should be possible to use the book for both a basic course for students who do not necessarily wish to go to graduate school, but also as a first semester of a more advanced course that also covers topics such as metric spaces.","contributors":[{"id":3669,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Jirí","middle_name":null,"last_name":"Lebl","location":"Oklahoma State University","background_text":"Jirí Lebl, Assistant Professor, Department of Mathematics, Oklahoma State University."}],"subjects":[{"id":86,"name":"Analysis","parent_subject_id":7,"call_number":"QA299.6-433","visible_textbooks_count":8,"url":"https://open.umn.edu/opentextbooks/%20/subjects/analysis"},{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":50,"url":"http://www.jirka.org/ra/","year":2020,"created_at":"2018-09-07T12:22:36.000-05:00","updated_at":"2021-01-03T17:43:26.000-06:00","name":"Jirí Lebl"}],"formats":[{"id":422,"type":"PDF","url":"https://www.jirka.org/ra/","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":423,"type":"Hardcopy","url":"https://www.lulu.com/shop/jiri-lebl/basic-analysis-introduction-to-real-analysis/paperback/product-21043650.html","price":{"cents":1462,"currency_iso":"USD"},"isbn":null},{"id":1981,"type":"Online","url":"https://www.jirka.org/ra/html/frontmatter-1.html","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":1982,"type":"LaTeX","url":"https://github.com/jirilebl/ra","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":3,"reviews":[{"id":271,"first_name":"William","last_name":"Newton","position":"Research Scientist","institution_name":"Colorado State University","comprehensiveness_rating":5,"comprehensiveness_review":"The textbook covers everything I would want to cover in a course at this level and some more. A teacher can use this book as the sole text of an introductory analysis class and skip the last two chapters for a slower class.","accuracy_rating":4,"accuracy_review":"I found a few minor typographical errors but no serious problems.","relevance_rating":5,"relevance_review":"This is exactly the material that should be covered in an introductory analysis class and it will remain relevant up to date for a long time.","clarity_rating":5,"clarity_review":"The material is presented in a clear, concise manner. Every term is adequately defined.","consistency_rating":5,"consistency_review":"The author does a great job of remaining consistent with terminology throughout the book. ","modularity_rating":5,"modularity_review":"It is difficult to write a highly modular textbook with this material since many results depend on earlier ones. However, this book does as good of a job as could be expected by breaking down the material into reasonable sections and maintaining a consistent numbering scheme throughout the book. When earlier results need to be referenced, they are easy to find.","organization_rating":5,"organization_review":"I am glad that the book opens with set theory. The lack of such material can be a shortcoming of some analysis texts. The chapters are presented in a logical order, with all of the material building on previous results.","interface_rating":5,"interface_review":"I had no trouble reading this book or finding results. I appreciate the use of a consistent numbering scheme for results throughout the textbook.","grammatical_rating":4,"grammatical_review":"I found a few typographical errors, but otherwise everything was fine.","cultural_rating":5,"cultural_review":"This material should be appropriate in any classroom where this subject is being taught. I saw nothing that seemed culturally insensitive. ","overall_rating":10,"overall_review":"This is a great textbook for introductory analysis, and I expect that I will use it the next time I teach the subject.","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":487,"first_name":"Sonmez","last_name":"Sahutoglu","position":"Associate Professor","institution_name":"University of Toledo","comprehensiveness_rating":4,"comprehensiveness_review":"This text covers all the standard material for a senior level undergraduate (or master level) real analysis class. It start with basics set theory and the real numbers. Then it develops supremum and infimum of bounded sets; limit, limsup, liminf for sequences; series of numbers and functions; continuity and uniform continuity of functions, derivative of functions,  Riemann integral and improper integrals, basics of metric spaces including connectedness, compactness set and continuity of functions between metric spaces. Finally it ends with a proof of fixed point theorem. The text covers all the main theorems (such as mean value theorem, intermediate value theorem, Heine-Borel theorem, Bolzano-Weierstrass theorem, Dini’s theorem) one would expect to be covered in this area. It includes a reasonable number of problems and examples. The text provides an effective index at the end.","accuracy_rating":5,"accuracy_review":"I did not see anything inaccurate.","relevance_rating":5,"relevance_review":"I don't expect the text to be obsolete any time soon as this is an advanced math textbook.","clarity_rating":5,"clarity_review":"The material is presented in a clear fashion and should be very readable by students.","consistency_rating":5,"consistency_review":"The style of the book is very consistent throughout the book.","modularity_rating":4,"modularity_review":"It is as modular as one can expect of a book on this subject. Since everything numbered consistently one can easily find the results needed from the previous chapters.","organization_rating":5,"organization_review":"The material is presented in a logical order. Definitions, theorems, examples, exercises, etc are all numbered in a consistent manner. The book is written in a little bit informal language but that is not a shortcoming.","interface_rating":4,"interface_review":"In general, the interface of this book is very typical of an advanced math textbook. All the statements are numbered  and hyperlinked making navigation very easy.","grammatical_rating":5,"grammatical_review":"Other then few typos I did not see any grammatical errors.","cultural_rating":5,"cultural_review":"This is not an issue for graduate level mathematics books and this book is no exception.","overall_rating":9,"overall_review":"This book has been approved by the  American Institute of Mathematics Open Textbook Initiative. I have used it twice in my classes and have been very happy about it. The author maintains an errata on his website and has been updating the text regularly. I suggest using the latest edition that can be obtained from the authors website.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":2525,"first_name":"Jeromy","last_name":"Sivek","position":"Assistant Professor - NTT","institution_name":"Temple University","comprehensiveness_rating":5,"comprehensiveness_review":"This book gives a very thorough coverage from set-theoretic prerequisites to difficult questions of the more advanced topics that students need for Real Analysis.  The proofs are helpfully detailed.  The little tricky parts are not skipped or left to the reader.  A professor trying to demonstrate rigor to their students will appreciate the choices made by the author.\r\n\r\nThe book has a good index and a comprehensive glossary.  The little touches are greatly appreciated.","accuracy_rating":5,"accuracy_review":"The book is well-written and has clearly been scrubbed of simple errors.  This is a book that I used with much success as a very young instructor who needed a solid base of material.  I developed confident that this book had correctly worked examples and proofs.","relevance_rating":5,"relevance_review":"This is exactly the material that a student needs to see in their first two semesters of introductory analysis.  It can be used as a first proof-based course coming after a linear algebra or possibly concurrently.  Different people will find it fitting their curriculum differently.  But this book provides a very nice two semester course that starts by introducing set theory and induction for the first time and ends with students ready for topology, measure theory, or more advanced calculus.","clarity_rating":5,"clarity_review":"The clarity of the writing is appreciated.  As a proof-based math text of course students will need to be guided through reading it.  But the pointers and language are arranged to maximize usability by a faculty person.  Because the book has some volume, an instructor can challenge their students to read some sections independently with confidence that the material is arranged clearly enough, obscured only by the usual challenges related to understanding analysis.","consistency_rating":5,"consistency_review":"This book sticks to its organizing principles.  The definition-example-proof-theorem-exercise setup is tried and true.","modularity_rating":5,"modularity_review":"Sections are broken into subsections in appropriate places.  It is appropriately self-referential in a way that is necessary for a book building up a mathematical theory.  The way in which some sections are optional is explained on the first page of the introduction.","organization_rating":5,"organization_review":"The text builds up the material in a sensible fashion.  Some of the ordering choices are the subject of lively pre-existing lively debates.  But all of the organizational choices here are logical and lead to a workable year if taken on order.","interface_rating":5,"interface_review":"I did not notice any interface issues.","grammatical_rating":5,"grammatical_review":"I do not remember being troubled by any grammatical errors.","cultural_rating":5,"cultural_review":"This book is not culturally insensitive or offensive.  Books in this subject rarely are.","overall_rating":10,"overall_review":"I recommend this book very highly.  I used it with much success as a first proof-based course for sophomore/ junior level students at Pitt.  You should give it a try.","created_at":"2019-01-14T20:52:02.000-06:00","updated_at":"2019-01-14T20:52:02.000-06:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/basic-analysis-introduction-to-real-analysis","updated_at":"2026-05-18T02:09:33.000-05:00"},{"id":135,"title":"Introductory Statistics","edition_statement":null,"volume":null,"copyright_year":2012,"isbn10":null,"isbn13":"9781453344873","license":"Attribution-NonCommercial-ShareAlike","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"In many introductory level courses today, teachers are challenged with the task of fitting in all of the core concepts of the course in a limited period of time. The Introductory Statistics teacher is no stranger to this challenge. To add to the difficulty, many textbooks contain an overabundance of material, which not only results in the need for further streamlining, but also in intimidated students. Shafer and Zhang wrote Introductory Statistics by using their vast teaching experience to present a complete look at introductory statistics topics while keeping in mind a realistic expectation with respect to course duration and students' maturity level. Over time the core content of this course has developed into a well-defined body of material that is substantial for a one-semester course. Shafer and Zhang believe that the students in this course are best served by a focus on that core material and not by an exposure to a plethora of peripheral topics. Therefore in writing Introduction to Statistics they have sought to present only the core concepts and use a wide-ranging set of exercises for each concept to drive comprehension. As a result Introduction to Statistics is a smaller and less intimidating textbook that trades some extended and unnecessary topics for a better-focused presentation of the central material. You will not only appreciate the depth and breadth of exercises in Introduction to Statistics, but you will also like the close attention to detail that Shafer and Zhang have paid to the student and instructor solutions manuals. This is one of few books on the market where the textbook authors have written the solutions manuals to maintain the integrity of the material. In addition, in order to facilitate the use of technology with the book the authors included “large data set exercises,” where appropriate, that refer to large data sets that are available on the web, and for which use of statistical software is necessary.","contributors":[{"id":2060,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Douglas","middle_name":"S.","last_name":"Shafer","location":"University of North Carolina","background_text":"Douglas Shafer is Professor of Mathematics at the University of North Carolina at Charlotte. In addition to his position in Charlotte he has held visiting positions at the University of Missouri at Columbia and Montana State University and a Senior Fulbright Fellowship in Belgium. He teaches a range of mathematics courses as well as introductory statistics. In addition to journal articles and this statistic textbook he has co-authored with V. G. Romanovski (Maribor, Slovenia) a graduate textbook in his research specialty. He earned a PhD in mathematics at the University of North Carolina at Chapel Hill."},{"id":2061,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Zhiyi","middle_name":null,"last_name":"Zhang","location":"University of North Carolina","background_text":"Zhiyi Zhang is Professor of Mathematics at the University of North Carolina at Charlotte. In addition to his teaching and research duties at the university, he consults actively to industries and governments on a wide range of statistical issues. His research activities in Statistics have been supported by National Science Foundation, US Environmental Protection Agency, Office of Naval Research, and National Institute of Health. He earned a PhD in Statistics at Rutgers University in New Jersey."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"},{"id":82,"name":"Statistics","parent_subject_id":7,"call_number":"QA273-280","visible_textbooks_count":30,"url":"https://open.umn.edu/opentextbooks/%20/subjects/statistics"}],"publishers":[{"id":45,"url":"http://www.saylor.org/site/textbooks/Introductory%20Statistics.pdf","year":null,"created_at":"2018-09-07T12:22:36.000-05:00","updated_at":"2018-09-07T12:22:36.000-05:00","name":"Saylor Foundation"}],"formats":[{"id":274,"type":"PDF","url":"https://www.saylor.org/site/textbooks/Introductory%20Statistics.pdf","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":275,"type":"Online","url":"https://saylordotorg.github.io/text_introductory-statistics/","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4","textbook_reviews_count":11,"reviews":[{"id":74,"first_name":"Leslie","last_name":"Burkholder","position":"Senior lecturer","institution_name":"University of British Columbia","comprehensiveness_rating":4,"comprehensiveness_review":"The consensus introductory statistics curriculum is typically presented in three major units: (1) Descriptive statistics and study design (first third of course), (2) Probability and sampling distributions (second third of course), and (3) Statistical inference (final third of course). This textbook covers all of these topics. Topic 1 is chapters 1 and 2. Topic 2 is chapters 3 through 7. Topic 3 is done in chapters 8 to 14. There are more chapters on the third topic. Inevitably instructors might not use them all. Each chapter comes with plenty of exercises and exercise answers. There is a good index and glossary. The coverage in each topic is very competent and clear. There is, however, nothing exciting or novel in the the manner in which the topics are covered or the pedagogical approach. Recent trends in teaching introductory statistics have emphasized statistics as a part of scientific investigations. So they have integrated the learning of statistics into the understanding of science. This text does little of that. An emerging trend is to make heavy use of computer simulation and even physical simulation techniques to aid learning. This text does none of that.","accuracy_rating":5,"accuracy_review":"Content is very competent, accurate, error-free, and unbiased. Instructors will find the many exercises are US-centric. They may find they want exercises that are not that.","relevance_rating":4,"relevance_review":"The content is fairly timeless in its coverage. It is certainly arranged in ways that would make altering it -- for example, to update it or make less US-centric it -- pretty straightforward.","clarity_rating":5,"clarity_review":"The textbook is very clear. The writing style is quite accessible. Many of our students do not have English as a first language. It doesn't look like the text would present issues for their understanding. On the other hand BCCampus might consider having the textbook translated into other languages as its contribution.","consistency_rating":4,"consistency_review":"The use of statistics terminology is consistent through the text. The organization of material is similar in each chapter","modularity_rating":5,"modularity_review":"The textbook is broken into smaller chunks. It looks like an instructor could skip or reorder sections without there being a problem.","organization_rating":4,"organization_review":"The writing in this text is clear and the organization of material is logical","interface_rating":5,"interface_review":"The text looks like a professionally published textbook. There isn't color and there aren't images. But in other respects it looks good. There aren't any navigation or user interface issues.","grammatical_rating":5,"grammatical_review":"I could find no grammatical or spelling mistakes in this text.","cultural_rating":3,"cultural_review":"The text is not culturally offensive in any way. The examples and exercises are often US-centric. rtsInstructors might want to adapt or modify these parts for a BC or Canadian audience","overall_rating":9,"overall_review":"As previously noted many examples and exercises are US-centric. There is no investigation of causal studies. This something some although not all introductory statistics cover.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":75,"first_name":"Shivanand","last_name":"Balram","position":"Senior Lecturer, Spatial Information Science","institution_name":"Simon Fraser University","comprehensiveness_rating":4,"comprehensiveness_review":"Most introductory statistics texts use the logical structure of descriptive statistics, probability, and inferential statistics to deliver the materials to new students. This Introductory Statistics textbook by Shafer and Zhang is no exception. There is an introduction chapter (chapter 1) that sets out the main definitions and conceptual foundation for the rest of the book. Descriptive statistics is covered in one chapter (chapter 2). Probability and related concepts are covered across four chapters (chapters 3-6). Inferential statistics (chapters 7-9) and their applications to statistical model building and testing (chapter 10-11) form the remaining parts of the content. Collectively these topics form a useful (and standard) foundation for learning statistics. The online version of the text contains a detailed and functioning hyperlinked Table of Contents for the Chapters and Section headings. I was unable to find a glossary or index, but maybe the same functional benefits can be obtained by clicking on the appropriate topic hyperlink and scrolling through the text. One aspect of the content that might be useful to include is the bigger picture notion of: How is statistics used in the real world? The examples and exercises sections provide some hints to students, but contemporary issues such as population growth, climate change and sea level rise are hardly ever mentioned. Including these issues and a connection to the statistical tools that can provide solutions to these problems would help make statistics fun for multidisciplinary students who often perceive statistics as boring and irrelevant. Another aspect of the content is the heavy reliance on the use of a calculator to perform many of the statistical calculations. Whilst this may have some value in terms of flexibility for the instructor as stated by the authors in the Preface, the reality is that once students pursue further statistics and other related courses they will be confronted with the needed to use computer software tools. Including this explicitly would have made the book more comprehensive and relevant to the modern statistics student. It should be noted that in the Large Data Set Exercises sections of the book there are some links to digital spreadsheet data that can be articulated as computer-based data analysis practice for students.","accuracy_rating":4,"accuracy_review":"The contents are free of errors. In the Acknowledgments section the authors listed at least 16 individuals linked to higher education that have provided feedback and suggestions for improving the materials. This adds confidence in the quality of the materials. Many of the exercises and examples use concepts (SAT scores for example) and data that are best understood within the context of the United States. Using the textbook outside of that geographic context may prove to be a limitation in terms of asking students to grasp an understanding of the problem domain before attempting a statistical solution. However, there are a few examples that attempt to break the mold - Section 2.5, Application 20 outlines a problem related to hockey pucks.","relevance_rating":4,"relevance_review":"The statistical core that the textbook focuses on is relatively stable and so changes would be few and far between. This statistical core is up-to-date. The examples and exercises that wrap around the statistical core could use some modifications. For example, issues (climate change, population growth, etc.) that appeal to a wider background of multidisciplinary students can make the entire book more relevant. Making these changes to the existing online HTML files would be relatively easy and straightforward to implement.","clarity_rating":4,"clarity_review":"The text is written in simple and clear prose. There are hardly any sentences more than 20 words long making the statistical messages easily digestible to students whose first language may not be English. Highlighted definition boxes and key takeaway boxes provide adequate explanations of terminology and key points.","consistency_rating":4,"consistency_review":"The quality, layout, terminology, sections and overall value of each chapter are all internally consistent. The online Table of Contents also provide a consistent means to access these materials in an easily accessible way.","modularity_rating":4,"modularity_review":"The text is highly modular. Each Chapter is broken down into smaller sections, and on the whole the materials are covered in a very efficient way making the chapters and sections relatively short. The Chapters are self-contained and can be re-ordered down to the Sections level to suit the needs of the instructor/curriculum.","organization_rating":3,"organization_review":"The topics are arranged in the standard statistical workflow process of Descriptive/Probability/Inferential/Modeling stages. There are a few instances where there is overflow of the topics from one chapter into another where it might not be a good fit. For example, an introduction chapter (Chapter 1) begins immediately to define core statistical concepts and to start familiarizing students with data presentation. The authors chose to continue data presentation (mainly histograms) in chapter 2 that has been titled Descriptive Statistics. In order to avoid any confusion in the minds of students, it would have been useful to focus the Descriptive Statistics chapter on mean, median, mode concepts. The histogram material could have been merged with the data presentation materials of Chapter 1, and maybe added newer presentation forms such as maps and sparklines, to have a more comprehensive data presentation chapter. Experience has shown that chunking materials using clearly defined boundaries help students to learn better. A particularly useful feature is the learning objective that has been given for each Section.","interface_rating":4,"interface_review":"The interface is well designed and organized to enable easy access and pleasing display of the materials. There is some color used throughout the text and this adds to improve the readability and contrast of the images and texts. It is fair to say that figures (especially graphs) are used extensively to illustrate the concepts being discussed.","grammatical_rating":4,"grammatical_review":"There is no evidence of grammatical errors. However, it should be noted that the online version of the material seems to be of the highest quality - the printed version of the book (of which I had access) had some symbols missing (Section 10.3) which might be due to the printing/conversion of certain of the Greek symbols used to represent statistical parameters.","cultural_rating":4,"cultural_review":"There is no evidence that the text is culturally insensitive in any way. I suspect that the book was designed to be used in the United States and so many of the examples are within that context. If the book is to be used for a student population outside of that context, then some changes (either by the authors or instructors) in the diversity of examples will be needed.","overall_rating":8,"overall_review":"Overall, this is a useful book. It does a good job at covering the breadth and depth of the topics one would expect for an introductory course. The content is well presented and easily accessible. The drawback is that statistical computing is not adequately emphasized and that students in Canada will find it a challenge to relate to some of the US-context questions and examples. Some immediate updates that are needed would be: (1) modify chapter 1 to show the links between statistics and real world solutions, (2) directly introduce computer software into the exercises, (3) adapt the questions and examples to be more relevant to an international audience.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":76,"first_name":"Erik C.","last_name":"Korolenko","position":"Professor","institution_name":"University Canada West","comprehensiveness_rating":3,"comprehensiveness_review":"The text covers some of the areas of the subject, albeit not in-depth. Whether this approach is appropriate for an introductory course, depends on the plan for the further study. Similarly to many other introductory textbooks, the text leaves open the question \"why\" do the particular formulas apply. Glossary is not provided other than chapter-by-chapter.","accuracy_rating":4,"accuracy_review":"The authors have gone great lengths towards ensuring error-free and unbiased content. As always in a text of this size, some errors would still creep in despite the best efforts. In particular: 1. Position of the mean on the illustration of a bimodal distribution (page 92) is incorrect. FWHM [full width at half maximum] and the variances for both Gaussian components of the distribution are identical, but the components have different amplitudes. As FWHM is identical, the mean should lie closer to the peak of the component with higher amplitude. Note, that if the FWHM of the left component was twice the FWHM of the right component, the position of the mean would nearly halfway between the modes. 2. Pages 224, 614: pictures and text inside are presented as mirror images of proper orientation. 3. Multiple pages: Authors use Gaussian distribution plots to illustrate Student distribution. While technically correct for large N, this gives a wrong impression about the shape of the Student distribution.","relevance_rating":3,"relevance_review":"Content is marginally up-to-date. No attention is given to non-parametric methods, Bayesian estimation, multivariate distributions, to name a few areas. The amount of included exercises is unnecessarily overwhelming, making the text appear much longer than it actually is, and difficult to locate the actual text material. Examples are easy to update, but would benefit from reduction of their count. The text will not become obsolete any faster than similar introductory statistics books.","clarity_rating":3,"clarity_review":"The authors have done a very good effort towards producing an easily readable and accessible text. However, the reader in most cases has to trust the word of the text as not a single proof is presented - even when this would be easy to achieve (Chebyshev theorem). This is a problem with similar introductory statistics textbooks that assume no prior knowledge of algebra.","consistency_rating":4,"consistency_review":"The text is quite consistent in its terminology and structure. However, the level of detail in presentation of the starting chapters much exceeds that for the last chapter (ANOVA).","modularity_rating":3,"modularity_review":"The text is clearly intended to be used in a sequential manner as it builds upon the prior knowledge chapter by chapter. Thus, it is better suited to truncation at the end rather than re-organization or dropping of the intermediate subunits.","organization_rating":3,"organization_review":"Topics in the text are presented clearly but require a leap of faith on the part of the reader in every instance a new formula is presented.","interface_rating":4,"interface_review":"The text has some inconsistencies in the layout of its components: 1. Overscripted variables are not typeset well in Word. 2. Formulas and text typeset in LaTeX on occasion import into Word with a loss of resolution (see the example 21, page 93). 3. As noted before, illustrations are heavy on the Gaussian distribution images, even where the Student distribution images are needed. 4. Navigation through the parts imported as images is visibly different from navigation through the parts entered as text.","grammatical_rating":5,"grammatical_review":"Grammar has been very well proof-read.","cultural_rating":5,"cultural_review":"The text is not culturally offensive or insensitive, and makes use of inclusive examples.","overall_rating":7,"overall_review":"The text presents a good attempt at presenting the introductory statistics topics for students with little previous experience with statistics and probability.\r\nThis review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.","created_at":"2013-10-09T19:00:00.000-05:00","updated_at":"2013-10-09T19:00:00.000-05:00"},{"id":340,"first_name":"Mamfe ","last_name":"Osafo","position":"Mathematics Instructor","institution_name":"Centrral Lakes College ","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers some of the areas needed for an Introduction to Statistics or Elementary Statistics. For example, experimental design was not well covered in chapter 1 which introduction to Statistics. Both the table of content and index was missing in this text, which makes it hard to know exactly what page you have to go and read the topic you want to. Lastly there was no set of instruction teaching students how to use technology to perform some of these computations. ","accuracy_rating":5,"accuracy_review":"I found the contents in the book to accurate and unbiased. I didn’t find any errors or inaccuracies. ","relevance_rating":5,"relevance_review":"Because of the well-structured contents in the textbook, it will be very easy to update it or make changes at any point in time. The content in textbook is up to date.","clarity_rating":4,"clarity_review":"The clarity in the book was very good for an intro to statistics course. The textbook is easily readable and the graphics are not bad at all. The language in the book is easily understandable. I found most instructions in the book to be very detailed and clear for students to follow. ","consistency_rating":5,"consistency_review":"The contents in the book is very consistent from beginning to the end. The contents in the book are well structured and well organized for each unit.","modularity_rating":4,"modularity_review":"The text is well sectioned into parts for students to read and understand. This textbook is highly modular, such that instructors combine or use different sections to teach the class and the students will still understand the material at a higher level. ","organization_rating":5,"organization_review":"The textbook is well structured and well organized","interface_rating":4,"interface_review":"The interface of the book is very good, however the graphics could have been improved by adding some good images and diagrams. There was no table of contents or index in the pdf version of the book. You can only see the table of contents through online, which would be a very hard to navigate to the appropriate chapters and sections in the book. ","grammatical_rating":5,"grammatical_review":"No grammatical errors were found. ","cultural_rating":5,"cultural_review":"I did not find any offensive cultural language in the textbook. ","overall_rating":9,"overall_review":"On the whole, the textbook would be a very good book to use for an introduction to statistics class or elementary statistics, however I would recommend the authors adding an in-depth experimental design  contents to Chapter 1. Secondly I would recommend the authors to add a table of content and an index to the textbook. \n\n","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":763,"first_name":"Amit ","last_name":"Verma ","position":"Adjunct Instructor ","institution_name":"University of North Carolina at Greensboro ","comprehensiveness_rating":5,"comprehensiveness_review":"When comparing numerous statistical textbooks to this book, the level of comprehensiveness is consistent with other material published and in some cases such as the use of examples it is actually more comprehensive than many of the published statistics textbooks for an introductory class. When I look for an introductory statistics textbook, I look for a book to include topics beginning with introductory descriptive statistics and transitioning into population sampling distribution and basic probability, and concluding with nonparametric and parametric inferential testing. This textbook does a great job transitioning from statistical topics and provides a robust discussion on each topic with a plethora of example problems and practice problems along with answers. Providing answers within a textbook is a plus because most other textbooks make you buy a solutions book, adding to unnecessary costs. Additionally, the authors have done a good job to list an index and glossary to assist in locating various sections within the text with ease. ","accuracy_rating":5,"accuracy_review":"I have utilized many introductory statistical textbooks in the past and have checked the content within this book with others and have found that the content is accurate. There appear to be no major problems with the theoretical information provided and the example problems associated with each chapter are error-free and consistent with the types of example problems in other textbooks. There also appear to be no major flaws with the solutions to the practice exercises.","relevance_rating":5,"relevance_review":"Given that this is an introductory statistics textbook, many of the theoretical topics such as formulas, definitions, concepts, etc. covered will not change over time and as a result this text book will not need to be altered within a short period of time. I currently use many textbooks for introductory statistics that are over 5 years old to write lecture slides and generate example problems and have found that many changes were not needed when using older books. This textbook has done a great job to introduce various topics in a robust manner and thus will not need too many updates. The only updates that could potentially be made over time are the use of new and more relevant real-world examples than what the text currently presents. The book is organized so well that it would be extremely easy to add new information or modify existing information very easy without disturbing the flow of the content that is currently presented.    ","clarity_rating":5,"clarity_review":"This textbook is written in an extremely simplistic manner. The jargon and terminology that is used is explained thoroughly especially as it pertains to definitions and concepts. All terminology is thoroughly explained with extensive narrative and in many cases figures, illustrations, and formulas are use as supplemental references to assist with making topics clear. When comparing this book with other introductory statistics textbooks, the manner in which content is presented and the reading level utilized within each chapter is very comparable and in some cases even more simplistic than other textbooks. ","consistency_rating":5,"consistency_review":"This textbook is extremely consistent internally. Each chapter is arranged in a very similar manner where the learning objectives are clearly stated followed by definitions, theories, or formulas and then a robust narrative. In each chapter, there are use of figures, illustrations, and numerous example problems that walk the reader through step-by-step problem solving strategies. Additionally, the chapters have a list of robust practice problems. Overall, all material presented in each chapter is consistent from chapter to chapter. ","modularity_rating":5,"modularity_review":"The modularity of the textbook is one of the best features that distinguish this book from others in the subject content area. The content for each learning objective is broken up into smaller pieces allowing for easy adoption within a course. Since the topics are broken up on a more granular level, it would be very easy to rearrange subunits without confusing the reader or creating a disconnect in the topics that are being covered. Often times I like to teach a few topics out of order or merge topics within various chapters together in order for me to explain material better. This book allows for me to have this flexibility since there many sub-sections or units. I also appreciate the fact that there are not many run on chapters where numerous topics are all introduced within a given section. ","organization_rating":5,"organization_review":"The topics are presented in logical order as necessary for an introductory statistics course. The book begins with descriptive statistics and spread of data and moves into population sampling and introduction to basic probability, followed by inferential statistical testing. This is commonly the flow of many comparable textbooks currently being used in the field. ","interface_rating":4,"interface_review":"There are no major navigation issues when I went through this textbook. I appreciate the face that you can download the book in a PDF format. At times it was a bit difficult to read the formulas that were presented in the boxes within some of the chapters, especially when symbols were used. While it was slightly to read at times, it is still manageable and not a major concern. ","grammatical_rating":5,"grammatical_review":"There were no grammatical errors that were observed when reviewing this textbook. Additionally, there were no major issues found with the example problems or the solutions to the questions within the various chapters. ","cultural_rating":4,"cultural_review":"This is not applicable. This book is consistent with other statistic books of its kind.","overall_rating":10,"overall_review":"This was an excellent textbook and a good alternative to books that need to be purchased at a high cost in student stores. I would recommend this book to be adopted as a cheaper alternative for introductory statistics courses. ","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":843,"first_name":"Russell","last_name":"Campbell","position":"Associate Professor","institution_name":"University of Northern Iowa","comprehensiveness_rating":4,"comprehensiveness_review":"I did not see any index or glossary.  It covers the basic descriptive statistics, probability, and inferential statistics of an introductory course.  There are no permutations and combinations.  The binomial distribution is presented as a formula without motivation for where the formula comes from.  The normal approximation to the binomial distribution with continuity correction factor is not presented.  (Of course, it uses the normal distribution for confidence intervals and tests of hypotheses for proportions later.)\n\nThe text does not cover bar charts or pie charts.  It does not discuss how to build histograms because software will do that.  \n\nIt is a comprehensive text, but goes light on (or omits) some topics which some instructors would like to cover.\n\nIt has a good selection pf problems, including answers to the odd numbered problems.","accuracy_rating":4,"accuracy_review":"On p. 381 it uses p-hat instead of p-nought to determine how large n must be for a test of hypothesis for a proportion.  It says you can use the normal distribution instead of the t-distribution if n \u0026gt; 30 (It has the standard table of the t-distribution for up to 100 degrees of freedom).","relevance_rating":4,"relevance_review":"I find it annoying that the authors expect the student to use the computationally efficient formulas for the variance, correlation, etc.\nOtherwise, it is a standard introductory statistics book with standard problems.","clarity_rating":4,"clarity_review":"I found no problem with the writing of the text. ","consistency_rating":4,"consistency_review":"Yes, it is consistent (including reliance on the computationally efficient formulae which I do not like).","modularity_rating":4,"modularity_review":"I used it as a pdf, hence am not sure how it could be modified.  But like any good statistics book, each chapter is broken down  into sections for each topic. You can easily identify the pages where a topic is presented. ","organization_rating":4,"organization_review":"It is the standard organization for an introductory statistics text.  Correlation and regression are at the end; that is where I cover it even in texts where it is chapter 4.","interface_rating":4,"interface_review":"I used it as a pdf, I am not sure whether there is an interactive version.  The graphics were fine, and it has the standard graphiccs for the normal distribution, confidence intervals, and tests of hypotheses.  There were acouple of typos like x-bar with the bar after instead of above the x in one place,but that was not a significant problem.","grammatical_rating":4,"grammatical_review":"I had no problems with the grammar.","cultural_rating":4,"cultural_review":"I did not notice any cultural relevance built into the text.  It is a statistics text, which is not highly dependent on culture.","overall_rating":8,"overall_review":"It is a basic introductory statistics text, but you should be prepared to supplement it if it misses a topic you like to cover.  The most annoying thing I find is the reliance on the computationally efficient formulae for the variance, etc.","created_at":"2016-12-05T18:00:00.000-06:00","updated_at":"2016-12-05T18:00:00.000-06:00"},{"id":1261,"first_name":"Sarah","last_name":"Clifton","position":"Instructor","institution_name":"Southeastern Louisiana University","comprehensiveness_rating":5,"comprehensiveness_review":"This text covers all the necessary points in an introductory Statistics glass with a well organized, user friendly index.  Each chapter has a nice summary of the glossary of terms.","accuracy_rating":5,"accuracy_review":"The content is accurate and error free.  The only comment I have is the notation is different than some textbooks so if using this as supplementation the faculty member make adaptations.","relevance_rating":4,"relevance_review":"Text concepts are current and could easily be tweaked in the future to prevent becoming a rather \"dated\" tool.","clarity_rating":5,"clarity_review":"The text is very clear but my recommendation would be to stick to traditional notation for some ideas.","consistency_rating":5,"consistency_review":"The book is very consistent with mathematical notations and the framework seems to follow the same format from chapter to chapter.  Consistent with math notation is very import so it is positive to see this in this condensed stat book.","modularity_rating":5,"modularity_review":"It would be very simple for a faculty member to select portions of the text and reorganize as needed.","organization_rating":4,"organization_review":"Although a few items were placed in a different position from standard Statistic books, the flow was logical.  For example, the Empirical rule is introduced later than traditional textbooks but blended well with the normal curve discussion.","interface_rating":5,"interface_review":"I actually looked at a few other math books online and decided to review this one.  I was pleasantly surprised how easily it was to navigate, click on tables and refer back to formulas.","grammatical_rating":4,"grammatical_review":"The text appeared to grammar free.","cultural_rating":3,"cultural_review":"This text was not culturally insensitive or offensive in any way but I do think it could have been a little more culturally diverse in it's examples.","overall_rating":9,"overall_review":"This book is an excellent resource for students.  This would make a very good supplement to another text and is very reader friendly.  I would suggest the homework exercises be numbered if possible so if a student had a question, it would be an easy reference point.  I also think if the graphing calculator ideas are going to be used, a few diagrams feature a \"screenshot\" of the calculator screen would be appropriate.  I especially like the answers to problems being easily accessed with the click of a button rather than flipping to the back of the book.  Many times in class, student's won't even check the answers in the back of the book although attempting the homework!   The review section for the course at the end of the book is very appropriate for the students at our institution and the answers are easily located.  This is a huge perk.\n\nFinally, I think this book has a great organization, nice examples, and almost a \"workbook\" approach to the homework helping students step by step.  Aesthetically, the book could use a few modern edges to make it easier for the student.  This might include an idea such as highlighting important formulas so it stands out.","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":2098,"first_name":"Debra","last_name":"Hydorn","position":"Professor of Mathematics","institution_name":"University of Mary Washington","comprehensiveness_rating":4,"comprehensiveness_review":"The text includes the usual topics for a one-semester course in the same order as many introductory statistics texts. Topics are well motivated and discussion usually includes useful diagrams or graphs when appropriate.  Each section includes a sufficient number of exercises.  Neither of the pdf or html versions has an index.  Users can conduct a word search but that can be awkward. Some topics are missing (e.g., midrange and midquartile for measures of center, how to find percentiles other than quartiles) but it is not uncommon to find lack of coverage of some topics in similar texts. Instructors who are familiar with the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (GAISE) will find this text appropriate for meeting the first three of six recommendations and all of the goals set out in this report. ","accuracy_rating":5,"accuracy_review":"The content is accurate.  I did not find any errors in the formulas, but the notation and terminology are sometimes non-traditional. For example, in hypothesis testing the level of significance is included as part of the alternate hypothesis rather than as a separate step in the testing process. As another example, residuals in regression analysis are referred to only as \"errors.\"  A third example is the method the authors use for determining if the sample size is large enough for conducting inference for a proportion. Like these examples, most of the other unusual features are minor in impact so that instructors can work around them. Solutions for the exercises at the end of each section appear to be error-free.  ","relevance_rating":5,"relevance_review":"The content is current with the traditional, non-randomization, approach to statistical inference.  The authors present the same formulas that are used in other similar texts.  As mentioned above, instructors who want to follow first three of the six recommendations in the GAISE guidelines will be able to do so using this text. ","clarity_rating":5,"clarity_review":"The text is very easy to read and the authors have provided good motivations for why and how the statistical methods are used.  Each section begins with a short list of learning objectives and ends with a list of key-take away concepts.  Definitions are set off from the text in boxes. The authors have done a good job in the first chapter of setting the stage to learn statistics. Throughout the text the authors provide explanations of how data is presented and used.  New concepts are well-explained and, in most cases, useful diagrams or graphs are included to support the explanations.  The use of formulas is demonstrated well. ","consistency_rating":5,"consistency_review":"The text is internally consistent.  When the authors refer to topics covered in previous sections they include links to those sections for easy reference. The links appear to be working correctly. ","modularity_rating":5,"modularity_review":"The Table of Contents in the html version allows for easy access to any section of the text. (I did not see a TOC in the pdf version, however.) The authors have divided up some topics into multiple sections, which might make it easier for students to learn.  There is just one link to the appendix that contains the normal, T and other tables, rather than separate links for each table. This is awkward but not too problematic. Like some other authors, the authors of this text have chosen to cover inference for a mean before inference for a proportion.  And like other texts, the authors don't provide as much detail about inference for a proportion as they do about inference for a mean.  If instructors want to cover inference for a proportion before inference for a mean, they would find it difficult to use this text.  But, this is the same problem instructors have with other similar texts. ","organization_rating":5,"organization_review":"The authors have chosen to cover topics in the same order as many other statistics texts.  For example, regression analysis is covered in a chapter later in the book after introducing statistical inference.  Instructors who want to cover correlation and regression earlier in the course, however, would be able to do so by skipping the section on inference for the slope.  ","interface_rating":4,"interface_review":"There are some large gaps between the numerator and denominator in some formulas that might cause confusion.  Also, none of the links to the large data sets exercises were working.  ","grammatical_rating":5,"grammatical_review":"No grammatical errors were found.  Explanations of statistical concepts are easy to understand and well motivated.  ","cultural_rating":5,"cultural_review":"The authors have chosen topics for examples and exercises that are typical of this kind of text.  These topics would be of interest to students and are appropriate for demonstrating the usefulness of statistics. ","overall_rating":10,"overall_review":"Students may like that the solutions to exercises are provided immediately after the exercises, but I think most faculty would prefer that they were less accessible. ","created_at":"2018-05-21T19:00:00.000-05:00","updated_at":"2018-05-21T19:00:00.000-05:00"},{"id":3930,"first_name":"Zhifang","last_name":"Yin","position":"Instructor","institution_name":"Bunker Hill Community College","comprehensiveness_rating":4,"comprehensiveness_review":"Overall the book is quite solid.\r\n\r\nfew things:\r\nno permutation/combination\r\nfor Binomial Distribution, no example for using second method\r\nno Poisson distribution,\r\nno normal approximation for Binomial and Poisson distribution\r\nSection, 7.2 maybe mention t distribution as the name of the section\r\n\r\nalso \r\ncould spent more time about how to use those tables\r\nmaybe more software technology\r\nno index , no glossary","accuracy_rating":5,"accuracy_review":"definition is accurate and well explained","relevance_rating":5,"relevance_review":"quite solid.","clarity_rating":4,"clarity_review":"Well explained, though maybe could use some more interesting examples; and maybe could use some definitions comparison etc.","consistency_rating":4,"consistency_review":"Yes, it is consistent","modularity_rating":4,"modularity_review":"I think so, it is good","organization_rating":4,"organization_review":"quite standard","interface_rating":4,"interface_review":"quite standard, of course could add some interactive links.","grammatical_rating":5,"grammatical_review":"very solid","cultural_rating":4,"cultural_review":"I didn't notice any offensive example, actually this book seems to have less word problem/example than other books.","overall_rating":9,"overall_review":"Overall it is quite a good book, maybe adding some more fun examples, or more technology for this course.","created_at":"2020-06-08T14:46:17.000-05:00","updated_at":"2020-06-08T14:46:17.000-05:00"},{"id":34534,"first_name":"Nabil","last_name":"Kahouadji","position":"Associate Professor of Mathematics","institution_name":"Northeastern Illinois University","comprehensiveness_rating":5,"comprehensiveness_review":"The text covers all material needed for an introduction and intermediate statistics course: starting with descriptive statistics, then the elements of probability theory needed for statistics, and finishing with a large portion dedicated to inferential statistics, where all topics of hypothesis testing and regression are covered.","accuracy_rating":4,"accuracy_review":"I am using this textbook as a second resource for an applied and computational statistics course (mainly for life sciences) with the use of technology (R). The textbook is suited for a statistics course for a general audience and without statistical software (like R). Therefore, the inferential statistics portion of the textbook relies heavily on the use of tables and on the rejection regions instead of the p-value. Also, the pooled variance is used for the testing hypothesis for the difference in means, which doesn't match the results that one can obtain using a statistical software (R), where the unpooled variance is used, and the degrees of freedom for the t-curve is not the typical approximation (sum of the sample sizes minus 2). Moreover, in many real-life data examples, the sample size are slightly higher than 30, but not large enough where using the normal distribution provides precision (instead of using the t-distribution).","relevance_rating":3,"relevance_review":"The contents is overall up-to-date, but the trend of using technology is increasing and application of statistics to real-life data is increasingly incorporated in  statistics courses, including technology component (R is an open and free statistical software used by many data scientists, and life scientists) seem to be inevitable in order for the textbook to remain relevant.","clarity_rating":5,"clarity_review":"The text is clear, examples are well designed, and the graphics provided in the text are of very good quality.","consistency_rating":5,"consistency_review":"The text is internally consistent.","modularity_rating":5,"modularity_review":"The sequencing of the chapters and the sections of each chapters work well. One can use independently a portion of the textbook easily as it used standard notation and widely used terminology.","organization_rating":5,"organization_review":"The sequencing and the organization of the text is clear and logical.","interface_rating":5,"interface_review":"No issues with the interface and no issues with images.","grammatical_rating":5,"grammatical_review":"Text is free of grammatical errors.","cultural_rating":5,"cultural_review":"No noticed issues.","overall_rating":9,"overall_review":"This is a very good introductory and intermediate statistics one-semester course. Content is comprehensive and its sequencing is logical. The exercises at the end of each section are balanced, starting with direct testing of the methods to application of statistics to real-life data. Moreover, solutions to half of the problems are provided (odd numbered problems), and even-numbered problems are fairly similar to the odd-numbered ones, which should allow students to work independently.  My only concern with the textbook is that it is well written for a course that doesn't use technology (statistical software) for the inferential statistics, and thus  many of the inferential statistics methods are relying on probability tables (focus on rejection regions instead of p-value, using pooled variance, approximate degrees of freedom). This being said, I use this text as a second textbook for a course tailored for life sciences with the use of technology.","created_at":"2023-04-30T11:27:58.000-05:00","updated_at":"2023-04-30T11:27:58.000-05:00"},{"id":35509,"first_name":"Mikheil","last_name":"Elashvili","position":"Assistant Professor","institution_name":"Bridgewater State University","comprehensiveness_rating":4,"comprehensiveness_review":"The textbook is quite comprehensive for an introductory level statistics course, it covers all the key topics. It is designed for a semester course, with a logical sequence of topics. The authors tried to avoid too much math and algebra to make it usable for readers with minimal math knowledge. Though it still requires knowing basic math concepts, such as graphs and mathematical expressions.  I would like to see more examples from practical applications and experimental design in more depth. Another significant gap may be a lack of software guidance or technology integration. This being said, I would use this textbook, but with added class material specifically on applications, experimental design, and technologies.","accuracy_rating":5,"accuracy_review":"The content I found to be generally accurate, unbiased, and free of errors. You may find some minor technical or graphical inaccuracies, such as illustration errors, non-traditional notations, etc. The solutions to sample problems, formulas, and drawings are consistent and mostly correct across the textbook.","relevance_rating":4,"relevance_review":"Core content is traditional for Introductory Statics, it remains stable and relevant. The only gap in terms of relevance can be the lack of integration with modern statistical software, applications, and limited coverage of real-world examples. Same concerns illustrations - use of animations or interactive graphs would make the Textbook more modern, but also more informative for students. Without the inclusion of tech-based methods or contemporary issues, its relevance may decline in the long term.","clarity_rating":5,"clarity_review":"Textbook is written in a simple language, with clear explanations and well-structured content. Definitions, theorems, and conclusions are highlighted. The review exercises at the end of each chapter are useful for self-assessment. It would be better to stick to traditional notations for some concepts.","consistency_rating":5,"consistency_review":"The book is internally consistent in mathematical notations, format, and terminology. Chapters are arranged in the same format, and I personally like it when learning objectives are specifically outlined at the beginning of each topic.","modularity_rating":5,"modularity_review":"The book is modular and well structured. Topics are broken down into a good size, digestible sections, which allows instructors to easily rearrange or skip units. The online version is convenient, with the Content table and links. Instructors can easily adapt the textbook to the class by skipping some topics or modules.","organization_rating":5,"organization_review":"Chapters are logically arranged in the standard order, beginning with data collection and descriptive statistics, then progressing through probability and inference. There are a few deviations in topic placement, but overall, the flow is coherent and usable.","interface_rating":4,"interface_review":"The book is easy to read and navigate online, especially in HTML format. Links and TOC would be good to have in a PDF file.  Some figures, graphs, and equations appear low-resolution and can not be zoomed in. No interactive graphs or multimedia resources (videos) are included. \nFor a more modern experience, instructors may consider pairing this text with online tools or simulations.","grammatical_rating":5,"grammatical_review":"I have not encountered any grammatical errors.","cultural_rating":4,"cultural_review":"The textbook is not specifically culturally insensitive, but it relies most on examples from US culture (like U.S. exams, pricing in USD, U.S. census data ... ) and could benefit from greater cultural diversity in examples and datasets.","overall_rating":9,"overall_review":"Introductory Statistics Textbook is a solid, accessible, and modular open-access textbook well fit for foundational courses in statistics. While it delivers strong content and organization, it lacks in some areas of technological integration, cultural range, and deeper real-world relevance. For instructors who supplement it with statistical software or interactive web content, it remains a highly usable resource.","created_at":"2025-06-06T16:45:09.000-05:00","updated_at":"2025-06-06T16:45:09.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/introductory-statistics","updated_at":"2026-05-18T02:09:29.000-05:00"},{"id":160,"title":"Applied Discrete Structures","edition_statement":null,"volume":null,"copyright_year":2017,"isbn10":null,"isbn13":"9781105559297","license":"Attribution-NonCommercial-ShareAlike","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"In writing this book, care was taken to use language and examples that gradually wean students from a simpleminded mechanical approach andmove them toward mathematical maturity. We also recognize that many students who hesitate to ask for help from an instructor need a readable text, and we have tried to anticipate the questions that go unasked. The wide range of examples in the text are meant to augment the \"favorite examples\" that most instructors have for teaching the topcs in discrete mathematics. To provide diagnostic help and encouragement, we have included solutions and/or hints to the odd-numbered exercises. These solutions include detailed answers whenever warranted and complete proofs, not just terse outlines of proofs. Our use of standard terminology and notation makes Applied Discrete Structures a valuable reference book for future courses. Although many advanced books have a short review of elementary topics, they cannot be complete. The text is divided into lecture-length sections, facilitating the organization of an instructor's presentation.Topics are presented in such a way that students' understanding can be monitored through thought-provoking exercises. The exercises require an understanding of the topics and how they are interrelated, not just a familiarity with the key words. An Instructor's Guide is available to any instructor who uses the text. It includes: Chapter-by-chapter comments on subtopics that emphasize the pitfalls to avoid; Suggested coverage times; Detailed solutions to most even-numbered exercises; Sample quizzes, exams, and final exams. This textbook has been used in classes atCasper College (WY), Grinnell College (IA), Luzurne Community College (PA), University of the Puget Sound (WA).","contributors":[{"id":3451,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Alan","middle_name":null,"last_name":"Doerr","location":"University of Massachusetts Lowell","background_text":"Alan Doerr, Professor of Mathematical Science at University of Massachusetts, Lowell."},{"id":3452,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Kenneth","middle_name":null,"last_name":"Levasseur","location":"University of Massachusetts Lowell","background_text":"Kenneth Levasseur, Professor and Chair, Department of Mathematical Sciences, University of Massachusetts Lowell."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":331,"url":"http://faculty.uml.edu/klevasseur/ads2/","year":2021,"created_at":"2018-09-07T12:22:39.000-05:00","updated_at":"2021-06-28T14:45:57.000-05:00","name":"Alan Doerr \u0026 Kenneth Levasseur"}],"formats":[{"id":648,"type":"PDF","url":"https://discretemath.org/","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":649,"type":"Hardcopy","url":"https://www.lulu.com/shop/ken-levasseur-and-al-doerr/applied-discrete-structures/paperback/product-23165305.html","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":650,"type":"Online","url":"https://discretemath.org/","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":3,"reviews":[{"id":1280,"first_name":"David","last_name":"Busekist","position":"Instructor","institution_name":"Southeastern Louisiana University","comprehensiveness_rating":4,"comprehensiveness_review":"The material adequately covers the subject and there is a reliable glossary and index.\nAs a text for an entry level survey class, it includes more than would generally be expected of a beginning college freshman.","accuracy_rating":4,"accuracy_review":"There are no major contextual errors in the text.  There are places where concepts are assumed to be in possession of the students without benefit of coverage\nNo discussion of parallel or perpendicular lines in linear equations; the notation 3/2x is confusing for slope, (3/2)x would be better\nTerminology of matrices (rows and columns) is assumed\nAssumes familiarity with graphing linear inequalities with no development and doesn’t address “test points”\nDoes not address any finance operations involving unknown times or number of periods of awarding interest\nUses three separate, unrelated notations for complements of sets\nError on page 221 – P(E | F is missing a closing parenthesis\nError on page 225 – centering for P(E | F) = P(E) for consistency\nError on page 279 – P(Walked Wednesday | Bicycled Monday) is not 3/5/16 and Bicycled misspelled in the next line (Bicycleed)","relevance_rating":5,"relevance_review":"The material is up-top-date with only minor references to “dated” entities in applications (Ma Bell and Pa Bell in Markov Chains);  the necessary changes would be quickly and easily made","clarity_rating":5,"clarity_review":"As far as a mathematics text goes, it is remarkably readable; there is minimal use of “technical jargon” beyond what is necessary to the material","consistency_rating":5,"consistency_review":"Language and content are consistent with other traditional texts; the framework and presentation, except where noted above flow well and topics are tied together as necessary","modularity_rating":5,"modularity_review":"There is little need to artificially subdivide given that the material is already fairly well sectioned out with topics appropriately arranged and flow from topic to topic is logical and developmentally arranged","organization_rating":5,"organization_review":"As discussed in previous sections, the material builds logically with necessary material covered adequately in most places to build new concepts.","interface_rating":4,"interface_review":"There is no real “artwork” in the presentation, no pictures or photographs.  Generally the tables and diagrams are well laid out (the exception being many pixilated tree diagrams and Venn diagrams in the material on Sets and Counting and Probability)","grammatical_rating":5,"grammatical_review":"One noted spelling error, as noted above (page 279);","cultural_rating":5,"cultural_review":"I find nothing in this presentation that would be offensive to anyone on the basis of race, creed, color, gender, religious or sexual preference","overall_rating":9,"overall_review":"I chose to look at this text because I regularly teach a Finite Mathematics class to entry level freshmen.  For my institution this is a survey course.  Some of the latter topics are well beyond the scope that would be covered, but I find them very interesting, nonetheless. \n\nPersonally, I would like to see some “artwork” added to the presentation, but it works fine without it.  I like there being both exercises and solutions for the exercises.  The presentation of solutions on a separate line, sometimes centered, sometimes not, doesn’t bother me but if I was paying for printing this book, I’d like to see a different layout that would reduce the number of pages,","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":1316,"first_name":"Michael","last_name":"Berry","position":"Professor","institution_name":"University of Tennessee, Knoxville","comprehensiveness_rating":5,"comprehensiveness_review":"I am pleased with the coverage of material that is needed for our COSC 312 (Discrete Structures) course. Index and glossary are fine. The chapters on Matrix Algebra are not really needed for our one semester course.  That material is covered in a linear algebra course offered by the Math Department.","accuracy_rating":5,"accuracy_review":"Content appears accurate but I did not evaluate all expressions in great detail.","relevance_rating":4,"relevance_review":"I am not convinced having the Sage programming examples is all that helpful. Our Computer Science students are taking this course the first semester of their junior year and they are already well versed in C++ and C.  I think it might be more useful to have a version of the book that does not have explicit programming examples. You could generate different versions based on what open source programming languages/environments the instructor has available.","clarity_rating":5,"clarity_review":"I had no concerns with the clarity of the text I read.","consistency_rating":5,"consistency_review":"The text is internally consistent in terms of terminology and framework.","modularity_rating":4,"modularity_review":"There are alignment issues with some of the equations extending way outside of the text margins.  Looks like LaTeX might have been used to create the pdf file for the book. Perhaps the margins could be widened a bit so that more text would appear per line within the PDF viewer.","organization_rating":4,"organization_review":"Yes, although I think the Matrix Algebra chapters could be more supplemental or even in an Appendix.","interface_rating":5,"interface_review":"Figures seem fine - just the margin issues I alluded to before.","grammatical_rating":5,"grammatical_review":"The text contains no grammatical errors from my reading.","cultural_rating":5,"cultural_review":"No problem whatsoever with cultural insensitivity.","overall_rating":9,"overall_review":"I appreciate the creation of this book for material that is still very needed for computer science curricula.","created_at":"2017-06-20T19:00:00.000-05:00","updated_at":"2017-06-20T19:00:00.000-05:00"},{"id":33784,"first_name":"Hellen","last_name":"Colman","position":"Professor","institution_name":"City Colleges of Chicago","comprehensiveness_rating":5,"comprehensiveness_review":"The text covers all areas in our Discrete Mathematics course appropriately and provides a useful index.","accuracy_rating":5,"accuracy_review":"This book is well written and rigorous while at the same time does a good job of motivating the material.","relevance_rating":5,"relevance_review":"Content is up-to-date and revised often.","clarity_rating":5,"clarity_review":"Well written and all notations are introduced before using them.","consistency_rating":5,"consistency_review":"The text is consistent and follows the logical outline of most Discrete Math courses.","modularity_rating":5,"modularity_review":"The text is well organized. The clickable expandable examples and exercises provide options for different reading levels.","organization_rating":4,"organization_review":"The flow is logical, except maybe with the exception of the chapter on Matrix Algebra that could be moved to the appendices at the end.","interface_rating":4,"interface_review":"The text is free of significant interface issues, including navigation problems. There are some distortion of some images in the Graphs chapter. The book may benefit from a more standardized way to unify the representations of graphs, Hasse diagrams, lattices, etc.","grammatical_rating":5,"grammatical_review":"I did not find grammatical errors.","cultural_rating":5,"cultural_review":"I did not find the text culturally insensitive or offensive in any way.","overall_rating":10,"overall_review":"The inclusion of SageMath notes in this textbook when Sage was first released was the reason for which I chose this book originally many years ago. It is an excellent example of successful integration of open source software in an open source textbook. With the different editions, these SageMath Notes have been expanded and they populate now most of the chapters of this book. It is great addition that rounds and expands its content.","created_at":"2022-04-11T18:52:03.000-05:00","updated_at":"2022-04-11T18:52:03.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/applied-discrete-structures","updated_at":"2026-05-18T02:10:09.000-05:00"},{"id":174,"title":"Introduction to Real Analysis","edition_statement":null,"volume":null,"copyright_year":2013,"isbn10":"0130457868","isbn13":null,"license":"Attribution-NonCommercial-ShareAlike","language":"eng","accessibility_statement":null,"accessibility_features":[],"description":"This is a text for a two-term course in introductory real analysis for junior or senior mathematics majors and science students with a serious interest in mathematics. Prospective educators or mathematically gifted high school students can also benefit from the mathematical maturity that can be gained from an introductory real analysis course. The book is designed to fill the gaps left in the development of calculus as it is usually presented in an elementary course, and to provide the background required for insight into more advanced courses in pure and applied mathematics. The standard elementary calculus sequence is the only specific prerequisite for Chapters 1–5, which deal with real-valued functions. (However, other analysis oriented courses, such as elementary differential equation, also provide useful preparatory experience.) Chapters 6 and 7 require a working knowledge of determinants, matrices and linear transformations, typically available from a first course in linear algebra. Chapter 8 is accessible after completion of Chapters 1–5.","contributors":[{"id":3663,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"William","middle_name":"F.","last_name":"Trench","location":"Trinity University","background_text":"William F. Trench, Ph.D. Andrew G. Cowles Distinguished Professor, Trinity University (Retired)."}],"subjects":[{"id":86,"name":"Analysis","parent_subject_id":7,"call_number":"QA299.6-433","visible_textbooks_count":8,"url":"https://open.umn.edu/opentextbooks/%20/subjects/analysis"},{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":256,"url":"http://digitalcommons.trinity.edu/mono/7/","year":null,"created_at":"2018-09-07T12:22:38.000-05:00","updated_at":"2021-01-17T11:29:01.000-06:00","name":"A.T. Still University"}],"formats":[{"id":168,"type":"PDF","url":"https://digitalcommons.trinity.edu/mono/7/","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":2228,"type":"LaTeX","url":"https://digitalcommons.trinity.edu/mono/7/","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"5","textbook_reviews_count":1,"reviews":[{"id":35293,"first_name":"Chad","last_name":"Scott","position":"Professor","institution_name":"University of Wisconsin-Superior","comprehensiveness_rating":5,"comprehensiveness_review":"This text comprehensively covers all of the content (and more) in a standard upper division undergraduate course in real analysis.","accuracy_rating":5,"accuracy_review":"It is very accurate with excellent, well constructed proofs and exercises.","relevance_rating":5,"relevance_review":"The text does not stray from the primary subject matter and the nature of the material provides for longevity.","clarity_rating":5,"clarity_review":"Trench (the author) has a very personable way of writing that invites the reader to relax.  Narrative between theorems brings the reader to a point where they are well position to possibly provide proof of the upcoming theorems themselves.  That, coupled with well done but not verbose proof writing style makes the text very clear for undergraduate consumption vs many commercially available texts I have used in the past.","consistency_rating":5,"consistency_review":"The writing style described in the clarity bullet above remains throughout the text.","modularity_rating":4,"modularity_review":"There is some self reference as is necessary in mathematics.  At times, one needs to refer to previously established lemmas in order to understand proofs being presented in a given section.  But, to the extent possible for mathematics, the material is nicely divided into components most teachers of real analysis would expect.","organization_rating":5,"organization_review":"The text flows nicely in a way that I believe most teachers of real analysis would expect.","interface_rating":5,"interface_review":"The interface is via pdf so the content is very stable.  I've not found any oddly distorted images or cutoff content.  The interface seems very clean.","grammatical_rating":5,"grammatical_review":"I've not found any significant errata.","cultural_rating":5,"cultural_review":"Texts on Real Analysis are a necessary staple for a good undergraduate degree in math.  This text fills that need without any perceptible cultural bias.","overall_rating":10,"overall_review":"I'd love someday to see this book in PreText so that it could be exported to more formats.  It's very well done.","created_at":"2024-10-29T12:06:18.000-05:00","updated_at":"2024-10-29T12:06:18.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/introduction-to-real-analysis","updated_at":"2026-05-18T12:03:49.000-05:00"},{"id":182,"title":"Combinatorics Through Guided Discovery","edition_statement":null,"volume":null,"copyright_year":2004,"isbn10":null,"isbn13":null,"license":"Free Documentation License (GNU)","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"This book is an introduction to combinatorial mathematics, also known as combinatorics. The book focuses especially but not exclusively on the part of combinatorics that mathematicians refer to as “counting.” The book consists almost entirely of problems. Some of the problems are designed to lead you to think about a concept, others are designed to help you figure out a concept and state a theorem about it, while still others ask you to prove the theorem. Other problems give you a chance to use a theorem you have proved. From time to time there is a discussion that pulls together some of the things you have learned or introduces a new idea for you to work with. Many of the problems are designed to build up your intuition for how combinatorial mathematics works. There are problems that some people will solve quickly, and there are problems that will take days of thought for everyone. Probably the best way to use this book is to work on a problem until you feel you are not making progress and then go on to the next one. Think about the problem you couldn't get as you do other things. The next chance you get, discuss the problem you are stymied on with other members of the class. Often you will all feel you've hit dead ends, but when you begin comparing notes and listening carefully to each other, you will see more than one approach to the problem and be able to make some progress. In fact, after comparing notes you may realize that there is more than one way to interpret the problem. In this case your first step should be to think together about what the problem is actually asking you to do. You may have learned in school that for every problem you are given, there is a method that has already been taught to you, and you are supposed to figure out which method applies and apply it. That is not the case here. Based on some simplified examples, you will discover the method for yourself. Later on, you may recognize a pattern that suggests you should try to use this method again.","contributors":[{"id":3629,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Kenneth","middle_name":"P.","last_name":"Bogart","location":"Dartmouth College","background_text":"Kenneth P. Bogart arrived at Dartmouth in 1968 after receiving his Ph.D. at the California Institute of Technology in that year. At the time of his death in 2005, Ken was in California on a sabbatical and working to complete revisions on his books, Introductory Combinatorics and Discrete Mathematics in Computer Science, while continuing his research on graph theory and partially ordered sets. During his career, Ken published nine books and over 60 articles. His many years of service to Dartmouth were marked by a dedication to teaching, which included participation in Math Across the Curriculum and his own grant for Teaching Introductory Combinatorics by Guided Discovery."}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":97,"url":"https://bogart.openmathbooks.org/","year":null,"created_at":"2018-09-07T12:22:37.000-05:00","updated_at":"2019-12-29T15:53:40.000-06:00","name":"Kenneth P. Bogart"}],"formats":[{"id":136,"type":"PDF","url":"https://bogart.openmathbooks.org/","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":1219,"type":"Online","url":"https://bogart.openmathbooks.org/ctgd/ctgd.html","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":1220,"type":"Hardcopy","url":"https://www.amazon.com/dp/1981746595/ref=as_li_ss_tl?ie=UTF8\u0026linkCode=sl1\u0026tag=matpuzwik-20\u0026linkId=5610a828d38019c2d0a1ba66e2ead34e","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":1989,"type":"LaTeX","url":"https://github.com/OpenDiscreteMath/ibl-combinatorics","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":2,"reviews":[{"id":178,"first_name":"Heath ","last_name":"Hart","position":"Instructor","institution_name":"Virginia Tech","comprehensiveness_rating":4,"comprehensiveness_review":"In order to comment on the comprehensiveness of the book, I first have to describe the book's unusual pedagogical structure:  the author poses a list of questions for each major topic beginning with questions that are simple and concrete and gently moving to questions that are more difficult and abstract.  Even when answers are given, they are often given in a sketch form for the student to complete; the \"Socratic\" approach indicates a potential dialogue between students and their mentor.\r\n\r\nSo the book is \"comprehensive\" in that it asks questions about a lot of topics appropriate for an undergraduate combinatorics class, but you should not expect to find many worked-out examples or completed proofs in the book.  \r\n\r\nThere is an index, but it is of limited use (see question 8).","accuracy_rating":4,"accuracy_review":"Apart from the significant errors in the book's index, there are few errors in the body of the text.\r\n","relevance_rating":2,"relevance_review":"Longevity of the book is an issue, due to the unfortunate circumstances of its creation.  The author of the text was killed in a vehicle accident during a sabbatical taken for the purpose of updating the text, and his family was not able to locate source files for the last printed version.  \r\n\r\nThere are source files available, but they represent an unfinished state of an intended next edition of the text; as the book's website explains, the PDF \"does not correspond to the current state of the source TeX files\".\r\n\r\nThis complicates the ability of an adopter to update or adapt the text.","clarity_rating":5,"clarity_review":"No issues; the tone is conversational, but can be precise when called-for.","consistency_rating":5,"consistency_review":"The \"framework\" of using long, deepening lists of questions is Bogart's choice of pedagogy, and he uses it consistently, possibly to the point of overwhelming a potential adopter who is inexperienced in teaching from this approach.  ","modularity_rating":3,"modularity_review":"Reordering would be difficult, because the nature of the material is developmental and new sections build on old.  Some reordering is possible, but the book offers no hints on how to do so effectively.","organization_rating":5,"organization_review":"This is one of the book's strong points. ","interface_rating":2,"interface_review":"The index lists page numbers that are off by a few pages for many topics; I surmise that there were some last-minute changes to the print edition that were not reflected in its index.  \r\n\r\nFor example, the index says the Pólya-Redfield Theorem can be found on page 269; it's actually on page 265.  Reading online and using the search function of your PDF reader is more reliable.\r\n\r\nOther, minor comments:  The author uses a nonstandard notation for the quotient n!/(k-1)!.  Color would have made some of the graphs easier to follow.","grammatical_rating":5,"grammatical_review":"Although I haven't scrutinized every page, I have not noticed anything objectionable in this area.","cultural_rating":3,"cultural_review":"Most of the examples involve vertices, functions, maps and similar mathematical objects; there are entire chapters that mention no people.\r\n\r\nThe author does not go out of his way to highlight contributions to the field by women or mathematicians of color.","overall_rating":8,"overall_review":"I have adopted this textbook for the junior-level combinatorics course that I teach, because the pedagogy is strong enough to overcome the mechanical defects in the index and the divergent state of the source TeX files.  My students respond positively to the book; they appreciate the cost, but they also find the book to be engaging.\r\n\r\nI've found it difficult to cover as much breadth and content with this book as I have with a more traditional book, but conversely, I believe the students emerge from the course with a deeper understanding of the content that we do cover.","created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":34798,"first_name":"Kristen","last_name":"Barnard","position":"Associate Professor","institution_name":"Berea College","comprehensiveness_rating":5,"comprehensiveness_review":"This text incorporates all areas that one would typically cover in an upper-level undergraduate course in Combinatorics.","accuracy_rating":5,"accuracy_review":"There may still be some typographical errors, but none that would impact understanding the material.","relevance_rating":5,"relevance_review":"The mathematical content is current.","clarity_rating":5,"clarity_review":"The whole point of this text is to learn through solving problems.  As such, it has to do a good job of introducing concepts clearly so that the reader can make their own examples.","consistency_rating":5,"consistency_review":"This text is focused on learning through guided inquiry, and it remains consistent throughout.  It delivers a minimal amount of information to set up the problem and then lets the reader discover the content.","modularity_rating":4,"modularity_review":"This text is generally linearly ordered, but it really needs to be.  It starts with no basic assumptions of the student as a combinatorist, and it gradually builds up the content.  There is little modularity in the content, but the chapters are well broken into subsections, easy to focus on for assignments and discussion.","organization_rating":5,"organization_review":"The text starts with no assumptions of the reader other than basic arithmetic skills, and gradually builds up to very sophisticated counting techniques.  Nothing seems disjoint or out of order.","interface_rating":5,"interface_review":"All formats of this book (print, pdf, and interactive text) are well designed for the student.","grammatical_rating":5,"grammatical_review":"Any grammar or punctuation issues are small and do not alter the understanding of the material.","cultural_rating":4,"cultural_review":"This text was originally written in the early 2000s and, like most math texts of that time and before, has issues on some problems in treating gender as a binary.  Otherwise it does not address cultural issues.","overall_rating":10,"overall_review":"I have used this text for quite a few years with students in an upper-level combinatorics class.  I believe strongly in inquiry-based education and good texts are hard to find.  I find that this one causes students to think, which is a good thing, but the level is not prohibitively hard for students that have not had previous experience with counting.","created_at":"2023-12-14T20:38:53.000-06:00","updated_at":"2023-12-14T20:38:53.000-06:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/combinatorics-through-guided-discovery","updated_at":"2026-05-18T02:09:48.000-05:00"},{"id":187,"title":"A Computational Introduction to Number Theory and Algebra","edition_statement":null,"volume":null,"copyright_year":2009,"isbn10":null,"isbn13":null,"license":"Attribution-NonCommercial-NoDerivs","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"All of the mathematics required beyond basic calculus is developed “from scratch.” Moreover, the book generally alternates between “theory” and “applications”: one or two chapters on a particular set of purely mathematical concepts are followed by one or two chapters on algorithms and applications; the mathematics provides the theoretical underpinnings for the applications, while the applications both motivate and illustrate the mathematics. Of course, this dichotomy between theory and applications is not perfectly maintained: the chapters that focus mainly on applications include the development of some of the mathematics that is specific to a particular application, and very occasionally, some of the chapters that focus mainly on mathematics include a discussion of related algorithmic ideas as well. The mathematical material covered includes the basics of number theory (including unique factorization, congruences, the distribution of primes, and quadratic reciprocity) and of abstract algebra (including groups, rings, fields, and vector spaces). It also includes an introduction to discrete probability theory—this material is needed to properly treat the topics of probabilistic algorithms and cryptographic applications. The treatment of all these topics is more or less standard, except that the text only deals with commutative structures (i.e., abelian groups and commutative rings with unity) — this is all that is really needed for the purposes of this text, and the theory of these structures is much simpler and more transparent than that of more general, non-commutative structures. There are a few sections that are marked with a “(∗),” indicating that the material covered in that section is a bit technical, and is not needed else- where. There are many examples in the text, which form an integral part of the book, and should not be skipped. There are a number of exercises in the text that serve to reinforce, as well as to develop important applications and generalizations of, the material presented in the text. Some exercises are underlined. These develop important (but usually simple) facts, and should be viewed as an integral part of the book. It is highly recommended that the reader work these exercises, or at the very least, read and understand their statements. In solving exercises, the reader is free to use any previously stated results in the text, including those in previous exercises. However, except where otherwise noted, any result in a section marked with a “(∗),” or in §5.5, need not and should not be used outside the section in which it appears. There is a very brief “Preliminaries” chapter, which fixes a bit of notation and recalls a few standard facts. This should be skimmed over by the reader. There is an appendix that contains a few useful facts; where such a fact is used in the text, there is a reference such as “see §An,” which refers to the item labeled “An” in the appendix.","contributors":[{"id":2858,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Victor","middle_name":null,"last_name":"Shoup","location":"New York University","background_text":"Victor Shoup is a Professor in the Department of Computer Science at the Courant Institute of Mathematical Sciences, New York University."}],"subjects":[{"id":83,"name":"Algebra","parent_subject_id":7,"call_number":"QA150-272.5","visible_textbooks_count":29,"url":"https://open.umn.edu/opentextbooks/%20/subjects/algebra"},{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":36,"name":"Pure","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":83,"url":"https://open.umn.edu/opentextbooks/%20/subjects/pure"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"}],"publishers":[{"id":118,"url":"http://shoup.net/ntb/","year":null,"created_at":"2018-09-07T12:22:37.000-05:00","updated_at":"2019-12-29T15:53:58.000-06:00","name":"Cambridge University Press"}],"formats":[{"id":887,"type":"PDF","url":"https://shoup.net/ntb/ntb-v2.pdf","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":3,"reviews":[{"id":459,"first_name":"William","last_name":"McGovern","position":"Professor","institution_name":"University of Washingon","comprehensiveness_rating":5,"comprehensiveness_review":"As promised by the title, the book gives a very nice overview of a side range of topics in number theory and algebra (primarily the former, but with quite a bit of attention to the latter as well), with special emphasis to the areas in which computational techniques have proved useful.  There is a very good index and glossary and a good review of notation and basic facts in the first chapter.","accuracy_rating":5,"accuracy_review":"The content is very accurate ad up to date.  I see no signs of bias.","relevance_rating":5,"relevance_review":"The format of the book makes it especially easy to update as advances in the subjects occur, particularly computational advances.  References are given to websites as well as books.","clarity_rating":5,"clarity_review":"The prose is very lucid and easy to follow.  Many examples are given and difficult ideas are introduced gradually.  The many relationships between number theory and algebra are explored in detail, each subject yielding important insights into and applications of the other.  No jargon is used and terminology is carefully explained.","consistency_rating":5,"consistency_review":"The book has a very consistent framework and a nice flow from one chapter to the next.  As mentioned above, relationships between the two subjects of the title are emphasized.","modularity_rating":5,"modularity_review":"The book is nicely broken up into manageable sections that would fit well into a lecture course.  Interdependences among chapters are clearly indicated.","organization_rating":5,"organization_review":"The topics are presented clearly and logically with relationships among them clearly pointed out and discussed in detail.","interface_rating":5,"interface_review":"All pages display very well on my screen, with no legibility or distortion issues that I could see.","grammatical_rating":5,"grammatical_review":"The grammar seems fine.","cultural_rating":5,"cultural_review":"This is not relevant for a mathematics text, but I saw nothing that would be offensive to a reader of any ethnic background.","overall_rating":10,"overall_review":"I would be happy to teach a course out of this book.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":485,"first_name":"Michelle","last_name":"Manes","position":"Associate Professor","institution_name":"University of Hawaii","comprehensiveness_rating":4,"comprehensiveness_review":"The text is so comprehensive that it feels overwhelming.  The author wanted to include all of the mathematics required beyond a standard calculus sequence.  However, the mathematical maturity required to read and learn from this text is quite high.  \n\nThe first two chapters cover much of a standard undergraduate course in number theory, built up from scratch.  However, it almost completely lacks numerical examples and computational practice for the students, which would give those new to the material time and experience in which to digest, assimilate, and understand the material.  I would think that a book targeted at this level of mathematical sophistication would assume students are comfortable with (for example) the most basic notions of group theory or the idea of equivalence classes. \n\nI can't imagine an appropriate audience for this text: one with the ability to read and work entirely at this abstract level but without any (or most) of the mathematical preparation provided in at least half the chapters.","accuracy_rating":5,"accuracy_review":"I found no mathematical errors.  The mathematical presentation is rigorous, clear, and well-explained.  It can be terse at times, skipping steps and making conceptual leaps that will be challenging for all but the very best students.","relevance_rating":4,"relevance_review":"The book covers both standard background that will always be relevant for these topics: the number theory and algebra background, the probability theory.  The computational chapters use pseudocode, so they will not be quickly outdated when new languages become fashionable.  Most of the algorithms studied are quite \"classical\" (as much as that makes sense for computer science), with modern ideas and developments usually relegated to \"Notes\" at the end of the computational chapters.  This will, of course, become outdated with new research in computer science.  But any faculty member who keeps up with the relevant research will be able to mention new developments to students, and it will not interrupt the flow of the ideas at all.","clarity_rating":4,"clarity_review":"The book is exceedingly well written, though it is at a very high level.  It is not \"friendly\" or \"chatty\" as you will find with many number theory books targeted to undergraduates.  For many students this will detract from clarity because they do not yet have the mathematical sophistication to work at this level.","consistency_rating":5,"consistency_review":"The book does an excellent job of consistency of notation.  For example, it starts with a development of number theory concepts, and develops notation for residue classes in the integers modulo n.  Later in the chapters on groups and rings, this same notation is used in more general situations.  Whenever there is the potential for confusion (for example, in using \"a mod b\" as a binary operation as is common in computer science versus using \"a is congruent to x mod b\" as is more standard in mathematics) the author is careful to point out the dual meanings and to warn the reader that there is some overloading of terminology.  It is unavoidable that this will happen in any book that treats both subjects seriously, and the author is careful with notation and keeps potential confusion to a minimum.","modularity_rating":4,"modularity_review":"The book has 21 chapters, each with several sections.  Most, but not all, sections end with a set of exercises.  Essential exercises are underlined (a very nice feature!) and optional sections are indicated with an asterisk.  What would be helpful would be some suggested paths through the text for various purposes.  I don't think it would be appropriate in any class to start at Chapter 1 and and work through all (or even most) of the content.  I imagine that most classes would skip the background material and head straight for the computational chapters, with the background there \"as needed\" for the students.","organization_rating":4,"organization_review":"My main comment about the structure is that the mathematics chapters and the computational chapters seem to be separated.  For example, the chapter on \"Congruences\" covers a tremendous amount of number theory, not all of which falls naturally (in my mind) under that heading.  Chapter 1 has a section on \"Ideals and greatest common divisors,\" but Euclid's Algorithm is not tackled until Chapter 4 (a more computational chapter).  As I read, I often felt \"now we are doing mathematics... now we are concerned with computational questions.\"  There are natural places of overlap (like Euclid's algorithm), and they are separated rather than treated more holistically.","interface_rating":4,"interface_review":"I read a standard PDF file.  There were a few hyperlinks (from the table of contents to section headings, for example), but not much else in the way of interface.  Everything was rendered clearly.","grammatical_rating":5,"grammatical_review":"I found no errors.","cultural_rating":3,"cultural_review":"There is a lot of interesting history and \"cultural\" notes in the computing chapters, and almost none in the more mathematical chapters.  A student who studied from this text would miss a lot of the standard \"mathematics culture\" communicated in a more traditional number theory course.","overall_rating":8,"overall_review":"My primary comment is that I cannot pin down the audience for this book.  I could not use this in an undergraduate number theory class; it is at far too high a level and moves far too quickly.  I could not use it in a graduate number theory class; it assumes no background at all and does not do some standard topics.  I suppose it would be useful for self-study by a very advanced student who already knew a good deal of mathematics and wanted to explore the computational side.  I do think that the title \"A Computational Introduction to Number Theory and Algebra\" is misleading at best.  Lacking numerical examples (for examples, students never actually do any \"clock arithmetic\" type calculations when introduced to the integers mod n) and with a focus only on abelian groups and commutative rings with unity, the book is simultaneously too sophisticated and not sophisticated enough for my use.  It also has a bit of a \"joyless\" feel in the mathematics, with a development of ideas and a writing style that never brings students into any part of the discovery of the mathematics.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":552,"first_name":"Emily","last_name":"Witt","position":"Assistant Professor","institution_name":"University of Kansas","comprehensiveness_rating":5,"comprehensiveness_review":"This text is an introduction to number theory and abstract algebra; based on its presentation, it appears appropriate for students coming from computer science.  The book starts with basic properties of integers (e.g., divisibility, unique factorization), and touches on topics in elementary number theory (e.g., arithmetic modulo n, the distribution of primes, discrete logarithms, primality testing, quadratic reciprocity) and abstract algebra (e.g., groups, rings, ideals, modules, fields and vector spaces, some linear algebra, polynomial rings and their quotients).  The book also includes an introduction to probability.  This, and other topics, are tools for interesting computational applications.  The Table of Contents indicates a few sections that are not required for future material.  The text includes an effective index.","accuracy_rating":5,"accuracy_review":"From my research in writing this review, I have not come across any major errors.  The author has a list of errata on his webpage.","relevance_rating":5,"relevance_review":"The book appears to be up-to-date, and includes some interesting applications of theoretical material to topics relevant in cryptography (e.g., the RSA cryptosystem, and primality testing).","clarity_rating":4,"clarity_review":"The presentation of topics is accurate, and starts \"from scratch.\"  All material necessary in future sections is included in the appropriate section.  Some sections are terse, and an instructor may want to supplement the theoretical exercises with some more computational ones.  The Euclidean Algorithm is presented after sections on solving linear congruences modulo n, and the Chinese Remainder Theorem; applications of the Euclidean Algorithm to these topics are presented later.  An instructor may want students to become comfortable with these topics initially through computations, using the Euclidean Algorithm.  We should also point out that mathematical induction is a prerequisite for this text, and some of the material is presented using pseudocode, which is different than many texts on these topics.","consistency_rating":5,"consistency_review":"The book's terminology and mathematical frameworks appear to be consistent.","modularity_rating":3,"modularity_review":"Since the book is quite long, an instructor for a one-semester course would need to choose specific topics from the text to cover.  There are a few sections indicated that are not required for future material.  However, even among the remaining sections, an instructor would need to carefully choose sections that include all necessary prerequisite material.   Depending on a course's focus, this could be done fairly easily.","organization_rating":3,"organization_review":"Each chapter is written in a logical manner, referencing previous material as needed.  The book jumps from chapters on purely algebraic topics to those focused on applications.  For this reason, an instructor may want to choose certain sections in a chapter to cover as prerequisites for an application, instead of covering the material linearly.","interface_rating":5,"interface_review":"There do not appear to be any problems with the interface of the PDF of the text.","grammatical_rating":5,"grammatical_review":"There do not appear to be major grammatical errors in the text.","cultural_rating":5,"cultural_review":"Due to the topics in this text, this question does not appear to be applicable.","overall_rating":9,"overall_review":null,"created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/a-computational-introduction-to-number-theory-and-algebra","updated_at":"2026-05-18T02:06:17.000-05:00"},{"id":196,"title":"Introductory Statistics","edition_statement":"2e","volume":null,"copyright_year":2023,"isbn10":null,"isbn13":"9781961584327","license":"Attribution","language":"eng","accessibility_statement":null,"accessibility_features":[],"description":"Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills.","contributors":[{"id":2757,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Barbara","middle_name":null,"last_name":"Illowsky","location":"De Anza College","background_text":""},{"id":5050,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Susan","middle_name":null,"last_name":"Dean","location":"De Anza College","background_text":""},{"id":5051,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Daniel","middle_name":null,"last_name":"Birmajer","location":"Nazareth College","background_text":""},{"id":6877,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Bryan","middle_name":null,"last_name":"Blount","location":"Kentucky Wesleyan College","background_text":""},{"id":6878,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Sheri","middle_name":null,"last_name":"Boyd","location":"Rollins College","background_text":""},{"id":6879,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Matthew","middle_name":null,"last_name":"Einsohn","location":"Prescott College","background_text":""},{"id":6880,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"James","middle_name":null,"last_name":"Helmreich","location":"Marist College","background_text":""},{"id":6881,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Lynette","middle_name":null,"last_name":"Kenyon","location":"Collin County Community College","background_text":""},{"id":6882,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Sheldon","middle_name":null,"last_name":"Lee","location":"Viterbo University","background_text":""},{"id":6883,"contribution":"Author","primary":false,"corporate":false,"title":null,"first_name":"Jeff","middle_name":null,"last_name":"Taub","location":"Maine Maritime Academy","background_text":""}],"subjects":[{"id":35,"name":"Applied","parent_subject_id":7,"call_number":"QA37.3","visible_textbooks_count":48,"url":"https://open.umn.edu/opentextbooks/%20/subjects/applied"},{"id":7,"name":"Mathematics","parent_subject_id":null,"call_number":"QA1","visible_textbooks_count":177,"url":"https://open.umn.edu/opentextbooks/%20/subjects/mathematics"},{"id":82,"name":"Statistics","parent_subject_id":7,"call_number":"QA273-280","visible_textbooks_count":30,"url":"https://open.umn.edu/opentextbooks/%20/subjects/statistics"}],"publishers":[{"id":95,"url":"https://openstax.org/","year":2024,"created_at":"2018-09-07T12:22:37.000-05:00","updated_at":"2024-03-03T14:54:54.000-06:00","name":"OpenStax"}],"formats":[{"id":131,"type":"Online","url":"https://openstax.org/details/books/introductory-statistics-2e","price":{"cents":0,"currency_iso":"USD"},"isbn":"978-1-961584-32-7"},{"id":132,"type":"PDF","url":"https://openstax.org/details/books/introductory-statistics-2e?Book%20details","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":133,"type":"Hardcopy","url":"http://www.amazon.com/Introductory-Statistics-Susan-Dean/dp/1938168208/ref=sr_1_10?s=books\u0026ie=UTF8\u0026qid=1405524130\u0026sr=1-10\u0026keywords=openstax","price":{"cents":3350,"currency_iso":"USD"},"isbn":null}],"rating":"4.5","textbook_reviews_count":37,"reviews":[{"id":174,"first_name":"Undupitiya","last_name":"Wijesiri","position":"Professor","institution_name":"Southwest Minnesota State University","comprehensiveness_rating":4,"comprehensiveness_review":"This book covers all necessary content areas for an introduction to Statistics course for non-math majors. The text book provides an effective index, plenty of exercises, review questions, and practice tests. ","accuracy_rating":4,"accuracy_review":"An overwhelming majority of the content is accurate. I found only couple of errors. The formula for finding the variance using grouped data is not consistent with the definition used. Assumptions for chi-squared tests were not mentioned.","relevance_rating":4,"relevance_review":"Content is up to date. It would have been better if computer software such as MINITAB or SPSS was used for the computations. This would help students learn how to interpret standard statistical outputs in practice. ","clarity_rating":4,"clarity_review":"The textbook is written with adequate clarity. Discussion on sampling distributions would have helped the flow of the content. Central limit theorem for a sample proportions is not included.  I think the authors rely too much on the graphing calculator for simple algebraic calculations. Should have used the normal and t-tables to find probabilities. ","consistency_rating":4,"consistency_review":"The notation used is consistent with standard notations used in the field throughout the text. However the formula used for finding variance of grouped data is not consistent with the definition. Poor notation is used in chapter 13 in discussion of ANOVA. Students may confuse the sum of the values in each group as the standard deviation in the group since the letter s is used for the sum. ","modularity_rating":5,"modularity_review":"The text is divided into easily readable sections. Content is well organized and presented in a manner so that reading sections can be assigned throughout the course. Different sections could be reorganized easily without presenting too much interruption to the reader.","organization_rating":5,"organization_review":"The material is presented with a flow consistent with a standard statistic text. Sample percentiles should have been discussed before discussing the median and quartiles. Overall content is organized and structured well. ","interface_rating":5,"interface_review":"I do not see any significant interface issues. Some of the formulas were hard to read because of distortion but it will not post any confusion for a careful reader. ","grammatical_rating":5,"grammatical_review":"I did not find any grammatical errors.","cultural_rating":5,"cultural_review":"I did not see any culturally insensitive material or exercises in the text.","overall_rating":9,"overall_review":"Overall a good text for non-math majors. Basic ideas such as experimental units, sampling distributions are not discussed. Relies too much on graphing calculators for simple algebraic calculations and finding probabilities. It is better to discuss percentiles before discussing the median and quartiles since they were defined later in the chapter.  Could have used statistical software for hypothesis testing, chi-squared tests, ANOVA, and regression. Plenty of examples, exercises, review questions, and practice tests were given in the textbook. Good lab assignments.","created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":186,"first_name":"Bill","last_name":"Heider","position":"Instructor","institution_name":"Hibbing Community College","comprehensiveness_rating":4,"comprehensiveness_review":"This book covers all the topics typically covered in an introductory level statistics course from an introduction to probability and the basics f study design through sampling distributions, confidence intervals, tests of one and two samples for  means, proportions and variances, the typical Chi square tests including independence, goodness of fit and homogeneity, regression and ANOVA.  It does not include non-parametric tests.  The p-value method is the only method utilized when performing hypothesis testing.  The critical value method is not utilized. One topic missing is s a discussion of determining normality of a data set. The index (and table of contents) in the pdf form of the text is especially useful as it allows the user to click on the page number in the index to scroll to the desired page.\r\n","accuracy_rating":5,"accuracy_review":"The work is free of errors.  Sample problems are drawn from a wide variety of subjects and topics.  ","relevance_rating":4,"relevance_review":"Use of the TI 84 calculator is emphasized. Directions for performing calculations on the calculator are included in the solution of example problems.    Most examples are generic in the sense that there won't be a need to update the data used.  Occasionally there is some data (for example one problem uses the population of Lake Tahoe NV and another uses information from a 2006 survey) that will date the book for users.  This does not in any way affect the relevance and/or appropriateness of the problem being taught, it may warrant a need to update with more current data to maintain interest of readers.","clarity_rating":3,"clarity_review":"Most explanations are clear but in some cases technology is relied upon to perform calculations.  For example, when performing the test for independence , it is explained how to calculate the individual terms yet to get the test statistic(the chi square) rather than showing that it is the sum of the individual terms the book states the sum is derived from use of a calculator or technology.  It seems it could have been clearer to the reader had the individual terms been shown rather than just being given directions of how to do the calculation using a TI-84 calculator where it does not seem at all clear where the final value is coming from.","consistency_rating":5,"consistency_review":"The book uses standard language used in statistics.  The book follows the same layout from chapter to chapter.  Terminology and symbols are explained.  Some Examples are worked in each section (where appropriate) with a problem for students to try interspersed among the explanations.  Calculator directions are included in the solution where appropriate.  There is also a summary of any of the statistics commands available on the TI83/84 family of calculators.  There are activities (\"labs\") at the end of each chapter followed by exercises for the entire chapter at the very end of each chapter (rather than the more typical problem set at the end of each section within the chapter).  The answer key is provided at the end of the chapter rather than at the back of the book that does make it easier to check solutions","modularity_rating":5,"modularity_review":"Each section of a chapter is easily covered in a day or two days at most.  One example of where the text departs from the order of most statistics tests is that the hypthesis test for variance is delayed until after the chi square tests are introduced.  If one wanted to include the topic with the other one sample tests it ould easilty be done.  Diferent options for ordering are given at the begining of the text.","organization_rating":5,"organization_review":"Each section follows the same structure.  Vocabulary and an explanation of the topic to be covered in the section followed by examples.  Calculator directions are included where they are needed in the solution of a problem.  Activities are included at the end of each chapter followed by a summary of key terms and the key concepts/topic for each section of the chapter.  A problem set for the chapter and then answers for odd exercises ended each chapter.  Once one becomes familiar with the layout it does make it fairly easy for one to search for information..","interface_rating":5,"interface_review":"The interface is wnderful.  The ability to click on page numbers in both the table of contents and the index and be moved to the appropriate page in the text is nice.  ALl text and imageas in the PDF format are very clear.  Highlighting f key concepts and ideas draws reader attention as does bold type for key terminology","grammatical_rating":5,"grammatical_review":"None. ","cultural_rating":4,"cultural_review":"Most examples are generic.  The examples were often relevent (distribution of populaitons bsed on race for a city were used once; opinion poll differrentieated by sex was used in another) but the topics were not offensive. ","overall_rating":9,"overall_review":"The book had links to external sources relevent to the topic.  Some video lectures were linked in an associated website.  a teaching guide is also available.","created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":197,"first_name":"Edward","last_name":"Dillon","position":"Instructor","institution_name":"Minneapolis Community and Technical College","comprehensiveness_rating":5,"comprehensiveness_review":"This textbook covers all of the standard topics usually covered in an undergradate introductory text including hyhothresis testing and ANOVA. The sequence is the same used in almost every such textbook. The index clearing describes the toppics covered. Each chapter ends with a glossary for that particular chapter.","accuracy_rating":5,"accuracy_review":"I randomly selected one example from each of the 13 chapters and worked through these finding no errors. The book includes extensive problem sets, \"Try It\" problems within the text after examples to give students practice, Review sets (Appendix A, for CH 3-13), practice tests and practice final exams (Appendix B). I did not spot any errors in the answer keys, though the real only way to vet so much content is to use the text. I did not spot any particula bias.","relevance_rating":5,"relevance_review":"This text is full of relavant data sets providing believeable real life examples for students. Many of the data sets are cited so that students can follow up at the original source, if they are interested. Many timely topics like wifi performance and West Nile virus are included. ","clarity_rating":4,"clarity_review":"The text is indeed writeen clearly, if not a little dry (as are most stats books). Key words are highlighted in bold to alert the reading to thei importance. The text is nicely chunked with examples and graphics to make it readable. The page spacing is ocassionally odd, for example there will be a title for a new sub-topic within a section and then a page break (example: p. 43 has the sub-topic title \"Simple Random Sample\", then the text to explain the idea is on the next page). I think they could clean this flow by simply using page breaks.","consistency_rating":5,"consistency_review":"The authors do not deviate from terminology and framework that is used in any of the popular intro stats textbooks put out by mainsteam publishers. The glossaries included could be used in any undergrad stats class that I have taught.","modularity_rating":5,"modularity_review":"As mentioned earlier in this review I think they do a really good job of organizing the sequence of topics and then chunking each section in a way that flows nicely so that students read about a topic, see an example and then have the opportunity to do a \"Try It\" example. I would be able to use it in my own stats class in the order that the chapters are given.","organization_rating":5,"organization_review":"They have organized similar to a multiitude of undergrad stats textbooks. One feature that I think is fairly unique is that they emaphaize organization of work. Undergraduate students often have trouble keeping thier work organized in a mathematics (or stats) course. The authors include graphical organizers for doing things like hypothesis tests for example. Students are offered a checklist approach to completing tasks (literally check lists). I like this.","interface_rating":4,"interface_review":"I did not find any real issues here other than what I mentioned earlier . . . that the flow is sometimes a bit odd with headings on one page and a misplaced page break separating the text from the heading. There is sometimes issues with the typography, usual involving symbols. For example on page 380, the bars above x-bar, the symbol for sample mean, is far away (above) the \"x\". This is likely to confuse students.","grammatical_rating":5,"grammatical_review":"I did not spot and such errors. I specifically read through ALL of the end of chapter glossaries.","cultural_rating":4,"cultural_review":"I did not spot any particular culturally sensitive or offensive material. I think that they could spice this text up with more examples involving issues of social justice, but that is just my personal preference in a stats text.","overall_rating":9,"overall_review":"The text includes instruction on the use of graphing calculators to do calculations, a technology used in many undergrad programs. The Group Projects in Appedix D are interesting and well thought out. They frenquently use error finding examples, a problem that contains errors which students work through to foster critical thinking.","created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":231,"first_name":"Jacqueline","last_name":"Joslyn","position":"Instructor/Teaching Assistant","institution_name":"University of Arizona","comprehensiveness_rating":5,"comprehensiveness_review":"The most important topics are covered. There are some concepts, like stem-and-leaf plots, that may be less critical for students in the social sciences to learn. Instructors can choose whether or not to skip the superfluous concepts. ","accuracy_rating":5,"accuracy_review":"I did not notice any glaring errors. There are some awkward word choices, which I discuss under \"grammar\".","relevance_rating":4,"relevance_review":"The content is up-to-date. There are references to studies conducted from 2009 to 2013. Several questions discuss smartphones and other modern technologies. These questions can be easily updated, but they may lose relevance within a short period of time. ","clarity_rating":3,"clarity_review":"This textbook is ideal for students who learn by reading. The instructions are a bit wordy, which might be confusing for some students. It would be an excellent choice for instructors who tend to deliver concise, visual lectures. Since mathematical symbols and equations are often verbalized and instructions are reading intensive, classroom time can be used to engage students in hands-on practice (e.g. showing them how to use the graphing calculator) and to break down the concepts and exercises into visual and mathematical models (e.g. writing down the equation and explaining how to interpret the notation). The instructor can spend less time explaining concepts and more time helping students to work on their quantitative and logical thinking skills.\n\nI appreciate that the textbook attempts to introduce students to various types of probability distribution functions in Chapter 4, but students may have trouble with some of these concepts because the information is not summarized or compared. Some chapters are written better than others. For instance, Chapter 11 is much more organized and readable. Different chi-square tests are explained separately, and then succinctly compared.","consistency_rating":2,"consistency_review":"Examples, questions, and chapter sections are organized consistently. The “Formula Review” sections are especially useful. Important rules of thumb are usually typed in bold. There are well-organized appendices at the end of the book. However, as a reference book, it does not fulfill my expectations. The writing style is inconsistent. Sometimes formulas are stated plainly, sometimes not. Mathematical jargon is introduced with varying degrees of precision and elaboration from chapter to chapter.","modularity_rating":5,"modularity_review":"It is very easy, and perhaps ideal, to pick specific chapters of this textbook to use in combination with other materials. Since the writing is inconsistent, it is not the best choice for instructors who prefer to teach from a single textbook. ","organization_rating":5,"organization_review":"The book is organized in the same way as other statistics textbooks.","interface_rating":4,"interface_review":"Interface issues are minimal. Occasionally, there are large spaces between items (for example, page 72). This can be a little distracting.","grammatical_rating":4,"grammatical_review":"The definitions of terms are satisfactory for the most part. However, there are segments of the book that are worded vaguely or oddly. For instance, the word “experiment” is often used to define words in the earlier chapters, which can be awkward. At one point, the authors state the tree diagrams are “used to determine the outcomes of the experiment” (188), but “event” might have been a better word to use than “experiment”. An advantage of this emphasis on statistical experiments is that it encourages the instructor to engage students in hands-on learning exercises, which introduces students to the rigors of collecting data. ","cultural_rating":5,"cultural_review":"The questions are culturally relevant to most U.S. students. Data on California is used fairly often. Chapter 9 includes some cute review questions written by students (sometimes in the form poems). ","overall_rating":8,"overall_review":null,"created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":239,"first_name":"Vance","last_name":"Revennaugh","position":"Associate Professor","institution_name":"University of Northwestern - Saint Paul","comprehensiveness_rating":5,"comprehensiveness_review":"The text covers most of the areas and ideas of an introductory statistics course,  The topics are covered at an appropriate depth.  I did not find any work on confidence intervals for the population variance or standard deviation, although there was a section on hypothesis teaching for a single population variance or standard deviation. Also, I did not find any discussion on non-parametic statistics.  The authors do cover geometric, hypergeometric, and Poisson distributions in detail.  The probability chapter did not cover Baye's Theorem or counting. Overall, the coverage and depth are satisfactory.  Also, I am able to find topics using the index and Table of Contents adequately.    ","accuracy_rating":5,"accuracy_review":"I could not find any typos. I feel the text was accurate, error-free, and unbiased.","relevance_rating":5,"relevance_review":"Content is up-to-date.  However I did notice an example using data from 1915 to 1964.  I feel the authors encourage the use of a graphing calculator and do not mention any other statistical software.  I feel the text is arranged in such a way that necessary updates will be relatively easy and straight forward to implement.   ","clarity_rating":5,"clarity_review":"I believe the text is very clear and understandable for students.  The authors explain and define statistic terms and concepts thoroughly.  There are also a sufficient number of examples to help explain the material.  The solutions to odd-numbered practice problems and homework problems are also provided at the end of each chapter","consistency_rating":5,"consistency_review":"The text is consistent in terms of terminology and framework.","modularity_rating":5,"modularity_review":"The text is easily and readily divisible into smaller reading sections.  I noted that the authors did place a hypothesis test for a single population variance or standard deviation in the Chi-Square chapter instead of the Hypothesis Testing with One Sample chapter.  The text should be easily reorganized and realigned without presenting much disruption to the reader.","organization_rating":5,"organization_review":"The organization of the text is very similar to other introductory statistics texts.  The topics are presented in a logical, clear fashion.","interface_rating":5,"interface_review":"I reviewed with a hard-copy of the text, so I cannot comment on this item.  I do plan to use the videos for the text in my online course.","grammatical_rating":5,"grammatical_review":"I did not notice any grammatical errors.","cultural_rating":5,"cultural_review":"I did not think that the text was culturally insensitive or offensive in any way.  Any names of people used in the examples are inclusive of a variety of ethnicities, races, and backgrounds.","overall_rating":10,"overall_review":"I plan to use this online text for an online course in the fall of 2015.  I am planning to use the online text for day school stats classes in the spring of 2016.","created_at":"2015-06-10T19:00:00.000-05:00","updated_at":"2015-06-10T19:00:00.000-05:00"},{"id":418,"first_name":"Jaejin","last_name":"Jang","position":"Associate Professor","institution_name":"University of Wisconsin, Milwaukee","comprehensiveness_rating":5,"comprehensiveness_review":"A Statistics textbook mostly have a standard structure.  This bookk covers major subjects of the course.\nCentral limit theorem is given a whole chapter, which is good because of its importance.\nHowever, I would like to see these more.\n\nNo explanation for Normal and other table use.  I understand we now mostly use computers for the table values; however, I believe, students still get benefit from the use of tables although it is an additional material to cover.\nNormality test would be needed. No Goodness-of-fit test or probability plot is explained.  Normality test is important for the inference statistics.\nIt would be good to explain mean and variance of linear combination of variables, such as E[5X+2Y]= 5E[X]+2E[Y].\nIt will be better to give a form of PDF (or PMF) of discrete random variables.\nConfidence Interval formula of F-distrbution would be better.\n","accuracy_rating":5,"accuracy_review":"This book is accurate.","relevance_rating":5,"relevance_review":"Elementary Statitics theory is not changed quickly.  Although the application examples can be more or less current, this book  is uptodated. ","clarity_rating":5,"clarity_review":"This book is clear in its contents.  This book is actually carefully written for better understandinig of the materials.","consistency_rating":5,"consistency_review":"Yes.  No problem.","modularity_rating":5,"modularity_review":"This book follows standard chapter layout of Statistics books (except that F-distribution is explained and used at the last part of the book).  Good concise sections with many problems helps understanding the materials.\n","organization_rating":5,"organization_review":"Yes.  Again, the standard structure of Statistics textbooks.\nExplanantions are simple and clear.","interface_rating":5,"interface_review":"No interface problems.","grammatical_rating":5,"grammatical_review":"Looks good.","cultural_rating":5,"cultural_review":"No problem.","overall_rating":10,"overall_review":"(1)\nThe competition of Statistics textbooks in the market is very high, and there are many good books available (at high prices).\nOne of the important aspects of the textbooks is the presentation, such as font, page layout and color.  To choose a book to review for my possible use in the near future, I selected this book because it caught my eyes among a few candidate books.  For example, this book has better use of colors, colorful boxes, and arrangement of tables to better guide the reading and understanding of the materials. This book has good details of the editing and has a very competitive presentation compared with other commercial Statistics textbooks.  This book is well written.  This book proves “a free textbook is not necessarily worse than more expensive books.”\n\n(2)\nIt is hard for a Statistics textbook to be better than others due to the large number of books available.  The most successful aspect of this book to me is the exercises.  They are carefully made to make students easily understand the lecture materials and get feeling of real statistical analysis.  The book also has very nice in-class exercises (Stats Lab) in all chapters. While this is very good for student learning, I wonder if an instructor can find time for this when covering the materials of the course. This book has many good features – such as key word summary and chapter review at the end of a chapter.  \n\n(3)\nThis book provides instructor resources such as syllabus, assignments, quizzes, exams, lecture videos and others.  Although these are popular with commercial textbooks, these features are certainly helpful. Especially, it provides nice assignments (or projects).\nThe lecture video, which is helpful, is partially based on hand writing.  I would prefer the video to be completely based on PPT.\nNo PowerPoint lecture note is provided.  This will make the preparation of lecture note time taking.\n\n(4)\nThe book explains the use of TI calculators; however, use of Excel will be more helpful for the students, both for descriptive Statistics and inferential Statistics. Although one book cannot have all possible contents, explanation of Minitab or Matlab will be helpful.\n\n(5) Editing\nThe numbers in tables can be centered for a better appearance.  \nThe “bar” notation of some variables (e.g., x_bar for sample mean) is away from the variable (e.g. x), which makes some equations less neat appearance. \nSolution of homework of each chapter is given in the chapter, which is nice.\n","created_at":"2016-01-07T18:00:00.000-06:00","updated_at":"2016-01-07T18:00:00.000-06:00"},{"id":582,"first_name":"Rudolf","last_name":"Lublinsky","position":"Instructor","institution_name":"Portland Community College, Oregon","comprehensiveness_rating":3,"comprehensiveness_review":"This textbook covers all of the standard topics usually covered in ? descriptive and inferential statistics textbooks for non- mathematicians. The sequence is the same used in almost every such book. All subject areas addressed in the Table of Contents are covered thoroughly.\n\nThe computational technology in this textbook is based on a specific brand of calculator (TI-83, TI-84) only. For using the textbook a student has almost evitable to purchase a calculator of this brand. Forcing students to buy a specific brand of calculator contradicts the very idea of saving money using OER. \nThe technologies offered in the text especially do not make sense for online class students who use the computer technologies and don’t need to purchase and use a calculator at all. I think some instructions for using of the Excel statistical functions have to be added in the book.","accuracy_rating":4,"accuracy_review":"The book is mathematically accurate, as far as I can see, but there are some minor errors. For example, in the formula of the confidence interval on page 417 there are the extra parenthesis in the wrong places. It gives wrong boundaries of the confidence interval.  In headlines of Ch. 9 on pages 482, 484, 503, 507, 510, and 518 words “Full hypothesis test” are misleading. I suggest that it should be “Null hypothesis test”. The definition of mutually exclusive events on page 172 is correct but it makes sense to clarify it for the case when events A and B are exhaustive events of a phenomenon.","relevance_rating":4,"relevance_review":"The introductory statistics doesn’t change quickly.  In general, the content is as up-to-date as any introductory probability textbook can reasonably be. Main change is in technology used for computation. The calculator references will be out of date rather quickly. For non- mathematician students a statistics course is a prerequisite and computing in this course should be supplemented by at least some simple computer technologies, Excel for example, to connect this course with using the statistics in the students’ next disciplines","clarity_rating":5,"clarity_review":"The clarity in the book is very good. The language in the book is simple and clear. The instructions in the book are detailed and easy to follow.","consistency_rating":4,"consistency_review":"The text is consistent in its terminology and framework. Despite a difference of topics in statistics and multiple authors of the textbook, notation, vocabulary, organization, structure and flow don’t vary widely in the chapters of the book.","modularity_rating":4,"modularity_review":"Chapters of the text are rather autonomous and each contains the explanation of key terms, notation, and some information from the previous chapters. I don't see any problems to divide the textbook into the weekly modules both in descriptive and inferential statistics.","organization_rating":5,"organization_review":"The organization is fine. The text book presents all the topics in an appropriate sequence. The structure of each chapter is done in the same fashion. This makes reading much easier. Due to the autonomy of chapters instructors can easily adjust the flow.","interface_rating":5,"interface_review":"I like the textbook interface. It is not monotonous; headlines of the different parts of the text are highlighted, bold or have a different color. The table of contents is allows direct access to the section but not vice versa.","grammatical_rating":5,"grammatical_review":"I’ve not found any grammatical errors in this textbook (but English is not my native language).  It is well written.","cultural_rating":5,"cultural_review":"There are some examples that are inclusive of a variety of races, ethnicities and back grounds. No portion of this text appeared to me to be culturally insensitive or offensive in any way, shape, or form.","overall_rating":9,"overall_review":"The textbook is a good book for introduction to statistics. Its Stats Lab fosters active learning in the class room. There are great number of examples, exercises in “Try it” and “Practice”. The language of the book is simple and clear. The graphing calculator is well integrated into curriculum. On the other hand sometimes the main stress is done not on conceptual understanding of statistics but on details of computational procedures for the specific brand of calculator and looks like a content of a calculator manual. The ignoring of the computer technologies is a weakness of the textbook.  \n\nThe textbook available to students for free and with addition of the computational computer technologies can be recommended for a community college basic statistics courses.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":594,"first_name":"Wendy","last_name":"Lightheart","position":"Mathematics Faculty","institution_name":"Lane Community College","comprehensiveness_rating":5,"comprehensiveness_review":"This textbook covers all of the usual topics you would expect to cover in an introductory statistics course for non-math majors. There is a glossary available at the end of each chapter, which is very helpful. A comprehensive index is available in this textbook at the end of the book, as you would expect. In addition, it's nice that a student may use the search option when using the pdf version of the textbook to search for specific terms.","accuracy_rating":3,"accuracy_review":"I've went through most of the textbook, but didn't thoroughly check the Try It or homework exercises. In the content and examples, I have found several errors, most of which are minor. I will be submitting those errors to add to the errata.","relevance_rating":5,"relevance_review":"The content is very relevant as it includes current studies and refers to today's modern technology and current events. It shouldn't be too difficult to update it with new studies and/or new technology and more current events in future versions.","clarity_rating":5,"clarity_review":"The textbook is very clear and concise, for the most part.","consistency_rating":4,"consistency_review":"Overall the book is fairly consistent in terms of terminology and framework. However, there are times when examples do not reflect the content exactly. For example, the histogram given in the solution to Example 2.9 does not follow the steps for making a histogram described previously in the content.","modularity_rating":5,"modularity_review":"The text is split up into subsections and smaller reading sections quite well. The blocks of text are appropriately small and manageable and most sections could be reordered without much difficulty to the reader.","organization_rating":5,"organization_review":"The topics are given in a very logical order. I particularly like how confidence intervals are covered for both a population mean (including t-intervals) and a population proportion before hypotheses tests for these parameters are explained. But if someone wants to cover both confidence intervals and hypotheses for a particular parameter together, then this can be easily done as well.","interface_rating":4,"interface_review":"Most images and display features are very good. However, there are some formatting issues that should be resolved. For example, each x-bar in the text has the bar located a significant distance above the x. Also, many times what should be subscripts are not displayed that way, which can be confusing for students who are trying to learn the massive amount of notation used in a statistics course.","grammatical_rating":5,"grammatical_review":"Of the errors I've found in this text, none of them were grammatical errors.","cultural_rating":5,"cultural_review":"I haven't found any issues with cultural insensitivity or offensive material in this textbook. The examples tend to include people from various ethnic backgrounds and people of different gender and races as well.","overall_rating":9,"overall_review":"Overall, I'm very happy with this textbook.","created_at":"2016-08-21T19:00:00.000-05:00","updated_at":"2016-08-21T19:00:00.000-05:00"},{"id":1056,"first_name":"Jonathan","last_name":"Bayer","position":"Associate Professor","institution_name":"Virginia Western Community College","comprehensiveness_rating":4,"comprehensiveness_review":"This book is sufficiently comprehensive for a non-majors introductory statistics course. In terms of content, it offers an adequate number of topics and adequate explanations. However, the book offers very little regarding sampling distributions and the relationship to the normal distribution.  There are enough example and homework problems to support the content. The index and glossary were also sufficiently comprehensive.","accuracy_rating":5,"accuracy_review":"I did not find any obvious errors in the calculations or formulas.","relevance_rating":4,"relevance_review":"I found the text contained an over reliance on the use of the graphing calculator. The textbook more or less requires the use of a graphing calculator. I think including a more substantial use of statistical software would have made the text more relevant. Students will find the use of data sets in the textbook and the citation of where to obtain them both relevant and helpful.","clarity_rating":5,"clarity_review":"The material is presented clearly. Some of the sections are a little bit “wordy” but this does not take away from the overall clarity.","consistency_rating":5,"consistency_review":"In the sections I reviewed, the notation and terminology was consistent.","modularity_rating":5,"modularity_review":"The organization and chunking of material in each section is appropriate for an introductory statistics student.","organization_rating":5,"organization_review":"The text is well organized. Each section I reviewed was presented in the same way. It begins with the objectives at the beginning of each chapter, proceeds through vocabulary and examples, and then ends with practice problems. It is organized similar to other statistics textbooks.","interface_rating":4,"interface_review":"The interface of the online version of the textbook works very well. Working through the contents tab you can access any section of the text quickly. The show solution/hide solution option makes it easy for students to attempt examples without looking at the solution. I did have problems when I attempted to visit one of the links to an external website.","grammatical_rating":4,"grammatical_review":"The text is “wordy”. I noticed the authors referenced certain ideas imprecisely. When referencing the outcomes of an experiment they failed to use the idea of a sample point and often used experiment interchangeably with event or in place of event when event was closer to the point. These mistakes did not take much away from the text and perhaps I am being a little too critical considering it is written for an introductory student.","cultural_rating":4,"cultural_review":"The text did not seem to be particularly culturally relevant. I did not find any evidence of it being culturally offensive.","overall_rating":9,"overall_review":null,"created_at":"2017-04-11T19:00:00.000-05:00","updated_at":"2017-04-11T19:00:00.000-05:00"},{"id":1151,"first_name":"Caitlin","last_name":"Finlayson","position":"Assistant Professor","institution_name":"University of Mary Washington","comprehensiveness_rating":5,"comprehensiveness_review":"The text covers all of the major concepts students would be expected to learn in an introductory statistics course including sampling and data, descriptive statistics, and inferential statistics. While the text might be overly comprehensive for a one semester statistics course, instructors could easily pick and choose which chapters and concepts to include or extend the course over two semesters. Each chapter includes a list of key terms alongside definitions. The text also includes an index as well as multiple appendices such as data sets and review exercises, which would be beneficial for students. The end-of-chapter reviews are also quite comprehensive and include a review of each section, reviews of formulas, and practice questions.","accuracy_rating":5,"accuracy_review":"The book appears to be accurate, error-free, and unbiased. It includes numerous examples and sample problems throughout the chapters, whose answers appear to be correct. The text also discusses common biases in statistical research, such as assumptions, sampling methods, and research ethics.","relevance_rating":5,"relevance_review":"The examples and data sets presented in the book help to make statistics relevant for students. Many of the examples reference university students and all are situated within real-world problems or issues. Most of the data sets are from several years ago (such as carbon dioxide emissions from 2009 and earlier), and it would be helpful if these were updated. However, the variety of examples and data sets provided make this book relevant and applicable to a variety of disciplines.","clarity_rating":4,"clarity_review":"This text emphasizes examples and sample problems over extensive narratives. The introductory text in each chapter is helpful and clear, but the descriptive text in the various sections of the chapter are often quite brief. It would be helpful if the chapter's narrative flowed a bit more cohesively from one topic to the next. That said, the emphasis on practice questions and examples would pair well with an instructor who could clearly present the concepts in class and then assign the textbook reading following the class meeting.","consistency_rating":5,"consistency_review":"The book's consistency is excellent and it follows a similar structure across all of the chapters. Each chapter includes numerous examples, and students would particularly find the examples with solutions followed by the \"Try It\" exercises without a solution immediately listed a helpful way to learn the material, practice it with guidance, and then try it on their own.","modularity_rating":5,"modularity_review":"This text includes a variety of core concepts in statistics that could easily be rearranged depending on instructor preference. As with any mathematical course, some concepts need to be introduced before others (the normal distribution, for example, is fairly critical in understanding hypothesis testing), but later concepts especially could be reorganized. In addition, less essential core concepts could be eliminated or reduced depending on the course objectives with little disruption to the reader.","organization_rating":5,"organization_review":"The text presents topics in a clear and organized way. Each chapter is similarly structured and presents core statistical concepts in a logical way, first introducing the concept, then providing examples, and finally offering sample problems for students to complete on their own in order to test their understanding.","interface_rating":5,"interface_review":"The text is well-presented with clear, simple diagrams and a consistent visual framework. The tables and figures enhance the concepts discussed and would aid in the reader's understanding.","grammatical_rating":5,"grammatical_review":"The text contains no grammatical errors and is well-written.","cultural_rating":5,"cultural_review":"The text contains a variety of culturally relevant examples, including many data sets and sample problems related to college students. At times, the examples could be adjusted so they are less culturally insensitive. A sample problem in Chapter 10, for example, refers to iPhones being more popular with \"whites\" than with \"African Americans,\" though some people prefer the label \"black,\" and this example overlooks or oversimplifies broader issues with income distribution. (iPhone purchases are not simply based on cultural preferences, though it's likely a contributing factor.) Perhaps instead of using different races in the example, the text could be revised to compare age groups. Otherwise, the examples include a variety of women and men as well as varying ethnicities and the issues discussed would be relevant for students of a variety of ages and life experiences.","overall_rating":10,"overall_review":"Overall, the text is highly comprehensive, covering a wide array of statistical concepts and including numerous examples and sample problems.","created_at":"2017-04-11T19:00:00.000-05:00","updated_at":"2017-04-11T19:00:00.000-05:00"},{"id":1160,"first_name":"Sandra","last_name":"Porter","position":"Math Instructor","institution_name":"Central Lakes College","comprehensiveness_rating":3,"comprehensiveness_review":"The text covers all of the topics that are included in the Minnesota Transfer Curriculum for an introductory statistics course.   Calculator instructions for the TI- graphing calculator family are included in each section. \nThe confidence interval chapter [Chapter 8] does not include finding confidence intervals based on standard deviations and variances.  The hypothesis testing chapter [Chapter 9] also does not mention testing for standard deviations or variances.  This chapter does spend a significant amount of time giving a good background on the concept of hypothesis testing which will improve student understanding for the rest of the topics.  \nType I and Type II errors are given good coverage with the introductory hypothesis testing.\nTable F1 includes an overview of typical English phrases that are often misinterpreted when trying to devise hypothesis statements.  Phrases such as, “x is no more than 4”, is illustrated to be equivalent to x = 4.  \nTable F2 includes a chart showing the symbols used throughout a statistics course and gives its meaning and the associated topic for its use.","accuracy_rating":4,"accuracy_review":"The content is generally accurate.  There are some minor typos which might lead to confusion for students.  A few noted below:  \nExample 5.8\nP(x \u0026lt; 5) = 1 – e(-0.25)(5) = 0.7135  should read\nP(x \u0026lt; 5) = 1 – e^(-0.25)(5) = 0.7135\nIn the paragraph following Figure 12.12, “the last two items at the bottom are r2 = 0.43969” should read “the last two items at the bottom are r^2 = 0.43969”\nExample 12.8\nFigure 12-15   r =  - 0.624-0.532, therefore r is significant, should read\nFigure 12-15   r =  - 0.624 \u0026lt; - 0.532, therefore r is significant.","relevance_rating":5,"relevance_review":"Statistics books that utilize actual studies are meaningful and demonstrate relevance to students.  This book does make use of studies and indicates where the information originates.\nThere are some problems that are included in Chapter 9 that are contributed by students of the author and are poetic in nature.  The relevance of these problems can be assessed by individual instructors.  \nNecessary updates should be relatively easy to implement.","clarity_rating":3,"clarity_review":"Overall, the text does well in explanations of the technical procedures.   Terminology is defined within context of the topic being addressed and is also included in a glossary at the end of the book.  The writing is at an appropriate level for this course.","consistency_rating":4,"consistency_review":"There did not appear to be any issues with consistency in terminology or framework.","modularity_rating":2,"modularity_review":"The organization of this book allows for smaller reading sections to be easily assigned.  Realignment of subunits should not provide disruption to the reader.","organization_rating":4,"organization_review":"The topics are arranged in an order that follows natural progression in a statistics course.  They are addressed logically and given adequate coverage.","interface_rating":4,"interface_review":"images/charts, and any other display features that may distract or confuse the reader.\nThe mean of a sample,   x ¯, in most of the text is written as x, with a bar written a substantial distance above it as demonstrated by the snip from the text at right. [unable to paste the snip to this document]   In other places, it is written as x ¯.  This makes for inconsistent spacing in the paragraph structure.\n\nListing the probability of A and B as P(AANDB) is not very readable.  [3.1 Terminology]","grammatical_rating":4,"grammatical_review":"I did not notice any grammatical errors, although better use of punctuation within sentences could improve readability.  Example: “you do not think Jeffrey swims the 25-yard freestyle in 16.43 seconds but faster with the new goggles.”  Possible revision:  “you do not think Jeffrey swims the 25-yard freestyle in 16.43 seconds, but faster with the new goggles.”   [Example 9.14]","cultural_rating":1,"cultural_review":"This text refers to many different cultures and ethnic backgrounds.  The examples are respectful of differences in our society.","overall_rating":7,"overall_review":"This textbook covers all of the required topics for transfer in the MNSCU [Minnesota State College and University] system.  It would work best for a lecture course, where it could be used primarily as a resource.  \nAn online student might have difficulty with the readability of the text in the absence of instructor guidance.  The margins are small to maximize the information that can be contained on each page.  The amount of information contained in a small space might prove intimidating for some students, especially those that are not comfortable with math as a subject matter.\nI would consider this text for adoption, but not without exploring other options that are available.","created_at":"2017-04-11T19:00:00.000-05:00","updated_at":"2017-04-11T19:00:00.000-05:00"},{"id":1764,"first_name":"Cathleen","last_name":"Battiste Presutti","position":"Lecturer","institution_name":"Ohio University Lancaster","comprehensiveness_rating":4,"comprehensiveness_review":"This text covers almost all of the concepts required in an introductory or sophomore level statistics course. \nHowever, there is one topic omission that I feel should be included in a future edition is combinatorics. The inclusion of general counting techniques would be beneficial to students and could easily be included in the chapter on probability. In the current edition of the text, it seems as though the authors either assume that students already know the combination formula used in the section on binomial distributions or will be relying so heavily on their calculators that explaining the formula is not necessary. \n","accuracy_rating":5,"accuracy_review":"Beyond the authors' errata which is available separately on textbook's webpage, I have found the textbook to be error-free and accurate.","relevance_rating":5,"relevance_review":"For the most part, I find that the subject matter in the examples and exercises to be up-to-date. There are a couple of  current \"hot button\" social/political topics and references to current technology that are incorporated into the exercises that I feel will be less relevant in a few years. However, they are few in number. Much of the subject matter used in the examples and exercises is timeless and would not need to be revised in order to make the text feel current. ","clarity_rating":5,"clarity_review":"The concepts throughout the text are explained appropriately and clearly. There is a nice balance between the clarity of the theory and the readability of the text. The prose format of definitions and theorems makes theoretical concepts more accessible to non-math major students without watering down the material.\n","consistency_rating":5,"consistency_review":"The text is consistent in its terminology and framework. ","modularity_rating":5,"modularity_review":"There are a few sections in chapters one and two that didn't need to stand alone and could have been combined with other sections due to the relationship of the topics in them. These were sections on data displays. And there was no individual section that would have been improved by separating into two sections. Overall, having the topics separated into smaller sections promotes synthesis of the material. ","organization_rating":4,"organization_review":"In chapter three, it seems more appropriate to cover section five (Venn diagrams and factor trees) along with counting techniques before starting probability theory.  I also believe that the topics in chapter twelve (linear regression and correlation) would be better suited to introduced before the chapters on probability distributions. Otherwise the remaining chapters of the text are appropriately and logically organized based on the material covered in an introduction to statistics course. ","interface_rating":5,"interface_review":"The text is free of any issues. There are no navigation problems nor any display issues.","grammatical_rating":5,"grammatical_review":"There are no grammatical errors.","cultural_rating":5,"cultural_review":"I found the text to be culturally respectful and inclusive with regard to gender, ethic background, etc.","overall_rating":10,"overall_review":"This text is a good introduction to statistical methods. It presents formulas and techniques in a clear way with detailed examples. \nThe theoretical depth of the material is at a level allowing students with a basic knowledge of algebra to understand the concepts while motivating deeper investigation for more mathematically advanced students.\n","created_at":"2018-02-01T18:00:00.000-06:00","updated_at":"2018-02-01T18:00:00.000-06:00"},{"id":1909,"first_name":"Jill","last_name":"Jamison Beals","position":"Assistant Professor","institution_name":"George Fox University","comprehensiveness_rating":4,"comprehensiveness_review":"Introductory Statistics includes all the topics critical to a first course in college statistics designed for a wide range of majors and programs. It is complete in its coverage of the entire statistical process from sampling to application of inferential statistics to generalizing and/or making a decision about a population of interest. For a semester long course, which does not allow covering all the of chapters, the comprehensiveness allows for picking and choosing the most relevant topics for the course. One aspect that is less complete is the sole focus on using the TI-83, 83+, 84, 84+ Calculator for computations. While complete in itself, applications of spreadsheets and probability tables are missing. \n","accuracy_rating":5,"accuracy_review":"I have not found anything that is inaccurate, in error or biased. \n","relevance_rating":5,"relevance_review":"The examples and exercises are such that they will not be out of date. There many references to specific colleges and locations that may seem irrelevant to students, but the examples themselves are lasting. The text includes examples and exercises that could be considered “triggers” and instructors should be aware of these, but they are not so intense to be considered inappropriate. Overall the text includes wide ranging subjects, issues, fields, and interests to be meaningful to a wide cross section of students. \n","clarity_rating":5,"clarity_review":"The textbook introduces new terminology, notation and formulas and concepts in each chapter while limiting excessive wordiness.  This is enhanced by the key terms, chapter review and formula reviews provided at the end of each chapter. In some cases, extra notation is avoided without loss of conceptual completeness, such as using OR and AND for probability statements rather than set notation for union and intersection. The verbal descriptions are concise and dense with many examples to fill out a reader’s understanding of an idea or concept.\n","consistency_rating":5,"consistency_review":"The text is consistent in layout and approach to topics. Terminology is used in a consistent way throughout the chapters. \n","modularity_rating":5,"modularity_review":"Each chapter has a clear introduction with distinct objectives. And while sections and chapters are ordered in a progressive manner, the text is self-contained enough so that sections and chapters can be presented in an order (or skipped) to serve overall course objectives. Exercises within chapters are also broken out by section, facilitating the assigning of only those exercises that practice desired topics.\n\n","organization_rating":5,"organization_review":"The text is organized such that concepts build on each other in a logical fashion. Within chapters, sections move back and forth between explanation and examples, also in a logical manner, addressing key points as appropriate to the flow of the text. \n","interface_rating":4,"interface_review":"The interface is sufficient, navigating around the text with table of contents is convenient.  At times page breaks chop up examples. The font choice and the layout of the online version makes for a more readable text than the PDF version and a better overall appearance. \n","grammatical_rating":5,"grammatical_review":"I have not found any significant grammatical errors in the text book.\n","cultural_rating":5,"cultural_review":"For use in the United States the text is relevant. While exercises and examples reference many different cultures (countries) most that have a culture specific reference are about US specific topics such as baseball, the US senate, presidential elections, income, etc. This enhances relevance for American students. \n","overall_rating":10,"overall_review":"I have used many statistics textbooks for an introductory stats class and find this textbook to be just as good as ones with high price tags, so being free to students makes it a good choice. One of the best feature is the Stats Lab activities/assignments included for each chapter. As is, or adapted, they make for in depth exploration into the given topic. \n","created_at":"2018-03-27T19:00:00.000-05:00","updated_at":"2018-03-27T19:00:00.000-05:00"},{"id":2107,"first_name":"Peter","last_name":"Orgas","position":"Adjunct Lecturer ","institution_name":"LaGuardia Community College","comprehensiveness_rating":5,"comprehensiveness_review":"Introductory Statistics is comprehensive and includes all the topics needed for an introductory course in statistics. In the preface, you are given options on how to strategical present the topics during the semester rather than follow chapter by chapter. The section on using the calculator is useful for the students, however, adding the probability tables instead of a link would be beneficial. ","accuracy_rating":5,"accuracy_review":"I found no inconsistencies, errors or bias throughout the textbook’s content. ","relevance_rating":4,"relevance_review":"The examples and data sets would appeal to a variety of students regardless of their major. It shows that statistical analysis is present in all areas of study. There were sections within chapters that focused too much on the use of the calculator. ","clarity_rating":5,"clarity_review":"The text was very clear. Students can read each section and get a good understanding of the topic due to the use of highlighted definitions and breakdown of problems. There are various examples for students to work out and get a better understanding. Chapter reviews and formulas help to sum out all the topics’ main ideas and terms before the exercises.   ","consistency_rating":4,"consistency_review":"I found all the chapters to be consistent in both layout and breakdown. ","modularity_rating":5,"modularity_review":"The chapters are separated into smaller topics which makes it easy to use all parts of the chapter if necessary. Also, the preface also gives you an option to use the chapters out of order to design your class differently than just chapter 1 then 2.etc., thus the textbook is structured to use the chapters you only need without losing the concepts. ","organization_rating":5,"organization_review":"The topics are presented in an order consistent with any high priced introductory statistics textbook I have used. ","interface_rating":4,"interface_review":"I found the interface to be very consistent and there were no images distorted.  ","grammatical_rating":5,"grammatical_review":"In the various chapters I reviewed. I found no grammar errors. ","cultural_rating":4,"cultural_review":"I found the textbook to be neutral with no insensitive or offensive materials. It appears very inclusive. ","overall_rating":9,"overall_review":"I found the textbook very useful and better than some high priced textbooks and plan on using it in upcoming semesters. ","created_at":"2018-05-21T19:00:00.000-05:00","updated_at":"2018-05-21T19:00:00.000-05:00"},{"id":2201,"first_name":"Kay","last_name":"Graves","position":"Assistant Professor","institution_name":"Fontbonne University","comprehensiveness_rating":4,"comprehensiveness_review":"This Introductory Statistics book covers all the introductory areas/concepts very thoroughly with the exception of Counting methods such as permutations and combinations.  These counting methods are not covered at all in the book and thus I must supplement this information into my course.","accuracy_rating":5,"accuracy_review":"Per my review and use, I have found no errors.","relevance_rating":5,"relevance_review":"This book could be used for many ears without any updates.  The examples are current and would continue to remain current for several more years","clarity_rating":4,"clarity_review":"Overall the text/concepts are written in a very clear manner.  The only concern I have is that several times when calculations are used, the formulas are not always given in the text but the reader must find the formulas at the end of the chapter.","consistency_rating":5,"consistency_review":"Text is consistent.","modularity_rating":5,"modularity_review":"Each section of each chapter is well organized.  While many sections of this (and other) intro stats books need to be followed in a order, there are several sections that could stand alone or be left out if time is short.","organization_rating":4,"organization_review":"The topics are presented in a typical, logical order for an introductory statistics course.","interface_rating":3,"interface_review":"The online interactive version of the book allows the students to work example problems and then click on the link to see if their work is correct.  But the biggest hang-up that I have with this book is that the homework or review problems are numbered in the truly online interactive version; the homework or review problems are only numbered in the PDF or book version.  This is a bit frustrating for the student to have to go back and forth between the two versions and for the instructor to assign work.","grammatical_rating":5,"grammatical_review":"Grammar is fine.","cultural_rating":5,"cultural_review":"This book has many examples and assignments that cover many different and diverse topics without being offensive or heavy in one area.","overall_rating":9,"overall_review":null,"created_at":"2018-06-19T19:00:00.000-05:00","updated_at":"2018-06-19T19:00:00.000-05:00"},{"id":2584,"first_name":"Patricia","last_name":"Swails","position":"Professor of Education","institution_name":"Oakland City University","comprehensiveness_rating":5,"comprehensiveness_review":"The text presents a comprehensive course in basic statistics.  There is an index as well as a glossary and reference list after each chapter.  Chapter sections are congruent across chapters, including collaborative exercises for group work, guiding questions a Statistics Lab, Try It guided practice, extensive practice problems based on real-world experiences, and homework.  Problem solutions are also provided. Ancillary materials include an instructor manual, Get Start guide, and PowerPoint.  Instruction includes key terms, statistical formulas, graphing, and calculator information. There is, however, no discussion of validity or reliability, nor is there any discussion of post hoc testing in the ANOVA chapter.","accuracy_rating":5,"accuracy_review":"The text is predominantly error free and unbiased.  There is a typo on page 456, listing both Goset and Gossett as the statistician’s name.  It makes a clear distinction between data and datum, which is commendable considering the current tendency to use data as a singular term.  The null and alternate hypothesis formats are a bit unusual, stating the null as less than and the alternate as more than, rather than the usual no difference or relationship for the null and increase/decrease or there is a difference or relationship leading to a two- or one-tailed discussion.","relevance_rating":4,"relevance_review":"The text is a traditional presentation of statistics that strongly supports its longevity.  The text is appropriate for advanced high school and bachelor levels as well as a graduate-level survey or resource for an advanced statistics course.  Information is also presented on IRB and ethics, not always found in statistics instruction.  Each chapter is thorough, including TI programming calculator instructions, but there is only a vague reference to statistical software with no direct mention of Excel or other statistical software such as SPSS.  The instructor can easily add computer software to the Collaborative Exercises.","clarity_rating":5,"clarity_review":"The instructional narrative is presented in a conversational style that helps those students intimidated by statistics.  The text thorough fulfills its purpose to help students design, implement, and analyze basic statistical concepts.  Key terms are presented in bold font.  Each chapter states specific objectives and learner outcomes.  Most importantly, the text explains the why as well as the how, much more than the basic, Do This.  Further, the text includes traditional formula notation, a feature often omitted in many statistics texts.","consistency_rating":4,"consistency_review":"The text is most consistent in the presentation of terminology.  There are some variations, however, such as the introduction of the Independent variable but no reference to the dependent variable.  Rather, the terms explanatory and response variables are used.  There is no mention of control, moderator, or intervening variables and uses the term, lurking variable rather than the traditional term, extraneous variable.  Skewness is presented as right or left skew with no mention of positive or negative skew except in a table. Further, the term, symmetric, is used early in the text then the term, normal, is used later in the text to describe distributions. Different terms are used in place of measures of dispersion and central tendency.","modularity_rating":5,"modularity_review":"The congruency of chapter components allows instructors and students to easily organize the learning environment.  Using the same sections in all chapters assures the instructor of a thorough coverage of any topic presented.  Each chapter includes objectives and learning outcomes to assist the instructor in identifying specific readings for a course or for ordering the chapters in a specific sequence.","organization_rating":5,"organization_review":"There is a logical sequence of chapters, but some instructors may find the Chi Square instruction out of place.  The chapter can easily be positioned between descriptive and inferential chapters without any loss in accuracy and clarity.  Chapters can be rearranged or omitted, depending on the course’s purpose.  Each chapter builds in complexity of narrative, formulas, problems, etc.\r\n\t\r\n","interface_rating":5,"interface_review":"The congruent structure of each chapter helps students anticipate the scope of instruction, practice, and other supports provided for each topic.  This ease of navigation also serves to decrease the anxiety level of statistics-phobic students. This text would be an excellent main text or ancillary text for online course delivery formats.","grammatical_rating":5,"grammatical_review":"The text does refer to GPA’s rather than the preferred GPAs.  The balance of information is error free.","cultural_rating":5,"cultural_review":"The instruction is inclusive, sensitive, and inoffensive.  The example scenarios are based on diverse, authentic studies.  Culturally-diverse populations, both genders, etc. are used in examples and problems throughout all chapters.","overall_rating":10,"overall_review":"Introductory Statistics is worthy of instructor review for a variety of secondary and post-secondary course work.  I am using the text for my basic statistics survey course.","created_at":"2019-02-25T13:00:28.000-06:00","updated_at":"2019-02-25T13:00:28.000-06:00"},{"id":2652,"first_name":"Kim","last_name":"Spayd","position":"Assistant Professor","institution_name":"Gettysburg College","comprehensiveness_rating":3,"comprehensiveness_review":"The very basic topics are included and a surprisingly large number of specific probability distributions. However, inferential topics are lacking. Sampling distributions are glossed over in a very unsatisfactory manner and their connection to inferential techniques is not made clear enough. Additionally, the coverage of confidence intervals is inadequate; only three intervals are discussed. In contrast, hypothesis tests are adequately covered.","accuracy_rating":5,"accuracy_review":"I found no factual errors.","relevance_rating":3,"relevance_review":"The content is standard and updates would be infrequent, if necessary at all. However, many of the examples are disappointingly banal. It is understandable that the authors would not want to include examples or references that might need frequent updating. But there are so many options for examples that are more interesting and appealing to college students.","clarity_rating":3,"clarity_review":"The prose and examples are very accessible but maybe too much so. The level of exposition is very low, leaving out many details that could explain choices made later. Such information would not necessarily be lost on an introductory statistics student; rather, I think it would make for a richer understanding of the mechanics of inferential statistics, which is the most useful part of the text.","consistency_rating":4,"consistency_review":"Vocabulary is repeatedly introduced but in different contexts; this could be confusing or helpful, depending on the person reading. ","modularity_rating":5,"modularity_review":"Sections are short and easily divisible for reading assignments. ","organization_rating":2,"organization_review":"The organization of the material is the biggest weakness of this text. A multitude of topics are introduced quickly within the same chapter or section, one right after the other, with little connection between them. Terminology is often reintroduced. For example, the median of a data set is described in the context of quartiles and the interquartile range, then later reintroduced in the section about measures of center. The interquartile range is not addressed in the section about measures of spread. Another example is the inclusion of Type I and Type II errors before finishing the mechanics of a hypothesis test. No adequate discussion of the probabilities of these errors can take place until much later in the text. Unfortunately, there are many more examples of the seemingly haphazard organization of the material. ","interface_rating":3,"interface_review":"Overall the interface is adequate. There are some tables that are split between pages (for example, moderately sized frequency tables) and some notation that is spaced oddly (for example, sample mean and standard deviation as well as z-scores for confidence intervals). Every so often, there is a page that is mostly blank for no clear reason.","grammatical_rating":5,"grammatical_review":"I found no grammatical errors.","cultural_rating":4,"cultural_review":"The examples generally avoid topics that could be considered even close to topical or controversial. The one caveat I have noticed, not limited to this text, is the repeated mention of gender binaries (boys and girls, men and women). Recognizing and including a category for people who identify as non-binary would be a step towards increased inclusivity.","overall_rating":7,"overall_review":null,"created_at":"2019-03-11T14:35:14.000-05:00","updated_at":"2019-03-11T14:35:14.000-05:00"},{"id":2893,"first_name":"Thomas","last_name":"Blamey","position":"Math Faculty","institution_name":"University of Hawaii Maui College","comprehensiveness_rating":5,"comprehensiveness_review":"I felt the textbook was as good as an publishers text in this introductory field.","accuracy_rating":4,"accuracy_review":"I did not see any glaring errors...and for the most part I felt is used common language an introductory text would use...\r\nAccept when the authors were introducing \"Confidence Intervals\".\r\nThey used uncommon language such as:\r\nEBM (this is not common and they should use a more common item such as \"E\" or \"ME\")\r\nerror bound (this is not common and they should uses \"margin of error\" as the vast majority of intro texts do)\r\nP′ =X/n  (they bounce back and forth on a \"cap\" X or not x...it should be non cap).\r\nThis would make it much easier for the majority of students who will be migrating on to the next course in this area of study.\r\n","relevance_rating":4,"relevance_review":"This area of study has changed little in recent times...and the text displays a \"standard\" delivery of the content.\r\nI would have love to see them include multiple technologies (not just the TI calculator).  I use Excel as it is the gold standard for desk-stations around the globe (although I understand many classrooms are not equipped with computing so the TI is the standard technology for \"Ed\").","clarity_rating":4,"clarity_review":"The text is written well and has an average communication level when delivering this material.","consistency_rating":5,"consistency_review":"The authors have done well to keep a consistent tone - difficulty when more than 1 author is involved.","modularity_rating":5,"modularity_review":"The text does a good job of following the market and breaking the topics into chapters that can be taken or re-arranged to suit most introductory courses.","organization_rating":4,"organization_review":"The organization is typical of this level of course - there is disagreement as to where \"correlation/regression\" should be placed (but the majority of texts at this level place it in the end - I would split this into \"descriptive\" and \"inferential\").\r\nThe \"descriptive\" could be included in Ch2 as a section.","interface_rating":4,"interface_review":"The interface is fine - it is a \"free\" text so one would not expect the top shelf pictures and images.","grammatical_rating":4,"grammatical_review":"Again...the only issues I saw here (minor) were the \"cap\" X or not when discussing sample proportion.","cultural_rating":5,"cultural_review":"The text seemed culturally neutral...","overall_rating":9,"overall_review":"I want to thank the authors for their work...I am actually using it in my University courses with MyOpen Math...\r\nAnd I am currently reworking the standard to fit my thoughts above and using data local to my community.","created_at":"2019-05-08T17:40:22.000-05:00","updated_at":"2019-05-08T17:40:22.000-05:00"},{"id":2897,"first_name":"Meryem","last_name":"Abouali","position":"Adjunct lectruer","institution_name":"LAGCC","comprehensiveness_rating":4,"comprehensiveness_review":"This book does contain a table of contents and the main components necessary to cover the average course in statistics. It provides an effective index. ","accuracy_rating":5,"accuracy_review":"The content is accurate. Formulas and definitions are accurate . There isn't any obvious numerical error","relevance_rating":4,"relevance_review":"The book is very relevant. the context is up to date. The text is written and arranged in such a way that necessary updates will be relatively easy and straight forward to implement. An instructor can supplement this with hands-on activities. Many of the examples are universal in nature and will still remain relevant for some time to come.","clarity_rating":5,"clarity_review":"The text is clear and provides adequate context for any technical terminology used. It is clearly defined in terms of the notation and symbol used.","consistency_rating":5,"consistency_review":"The text is consistent in terms of terminology and framework.  The layout of each chapter is consistent . The reader quickly can become familiar with how each chapter is presented and knows what to expect.","modularity_rating":4,"modularity_review":"It is nicely laid out and can be no problem modularize it depending on an instructor's preference. . The text is readily divisible into smaller reading sections that can be assigned at different points within the course. On a larger scale, the chapters are organized logically and in a manner consistent with other similar texts.","organization_rating":5,"organization_review":"The topics in the text are presented in a logical , clear fashion. The statistical concepts are presented inn  a clear and logical order and the flow is logical too.","interface_rating":5,"interface_review":"The interface is base on PDF format which is convenient for students and allows them to download the text to their laptops, tablets, ...etc","grammatical_rating":5,"grammatical_review":"The text contains no grammatical errors.","cultural_rating":4,"cultural_review":"The text is not culturally insensitive or offensive in any way . It should make use of examples that are inclusive of different races , ethnicity of different background.","overall_rating":9,"overall_review":"Overall, the text does the job for which is written for  and covering most of thee necessary topics needed for introductory statistics course.","created_at":"2019-05-10T15:06:38.000-05:00","updated_at":"2019-05-10T15:06:38.000-05:00"},{"id":3243,"first_name":"Jamie","last_name":"McGill","position":"Assistant Professor","institution_name":"East Tennessee State University","comprehensiveness_rating":5,"comprehensiveness_review":"The text is comprehensive for an Introduction to Statistics course. The topics include what is typically taught in a freshman level Probability and Statistics course. I compared the topics with those taught from our current textbook and there is no difference in coverage. ","accuracy_rating":5,"accuracy_review":"The book is accurate and complete in examples and information. No errors or bias noted. A good attribute of online textbooks is that if an error is noticed, it can be fixed quickly. ","relevance_rating":4,"relevance_review":"The text presents the topics in a way that will not become obsolete. Because no statistical software is included in the textbook, the instructor always has the option to introduce the software preferred at the time. Various calculators are mentioned, again because there isn't only one, the textbook will withstand time. ","clarity_rating":5,"clarity_review":"Definitions and summaries are included in each chapter. The text is written in a clear manner and is easy to understand. ","consistency_rating":5,"consistency_review":"The book follows the same basic structure for all chapters, making it consistent and easy to follow within each chapter. ","modularity_rating":5,"modularity_review":"The chapters could easily be reorganized while still making sense. This allows the instructor some flexibility in covering the material. ","organization_rating":5,"organization_review":"The arrangement of topics is presented in a logical manner. The topics are organized for an easy flow from chapter to chapter. Within each chapter, there is the same structure and arrangement. Again, this helps with the transition from chapter to chapter. ","interface_rating":4,"interface_review":"Overall, the interface is adequate. Slight distortions of images/tables are not significant nor confusing when reading through the chapters. ","grammatical_rating":5,"grammatical_review":"I did not see any grammatical errors. ","cultural_rating":5,"cultural_review":"Examples are culturally inclusive. I noted no offensive or insensitive wording or examples. ","overall_rating":10,"overall_review":"Being an OER textbook, it is a much better deal for the students than the traditionally published text that is often used. This text covers the same topics and links to an online homework platform if that is desired. It appears to be comprehensive as a textbook for a non-calculus based statistics course. ","created_at":"2019-10-31T23:11:02.000-05:00","updated_at":"2019-10-31T23:11:02.000-05:00"},{"id":3527,"first_name":"Rachel","last_name":"Keller","position":"Adjunct Instructor","institution_name":"Radford University","comprehensiveness_rating":5,"comprehensiveness_review":"This book is quite comprehensive for an introductory course.  Many topics that are not typically covered in a survey course are included (e.g., the geometric, hypergeometric, and exponential distributions are included in addition to the ubiquitous binomial, poisson, and normal distributions).  Furthermore, there is an extensive collection of supplemental resources for both the student (e.g., calculator guide, formula sheets, descriptions of mathematical phrases and symbols) as well as the instructor (e.g., data sets, practice exams, projects).","accuracy_rating":5,"accuracy_review":"The content of this text is adequately accurate and unbiased.","relevance_rating":5,"relevance_review":"The fundamental concepts covered in this text are classic and likely to withstand the test of time.  What distinguishes statistics textbooks from various decades is not the tests, distributions, or even necessarily terminology, but rather the technology and the datasets.  This text illustrates data analysis with the current technological standard of the TI calculator series, which has all expectation of remaining current for some time.  A majority of the provided data for examples is based on demographic/social/educational data (e.g. heights, pizza delivery times, test scores) that are unlikely to become problematically dated so as to obfuscate the underlying statistical process.  When specific dates and data are provided, they seem to be largely representative of the most recent decade and updates would be straightforward to implement if desired.","clarity_rating":4,"clarity_review":"The prose of the text is lucid and accessible.  Key terms and formulas are offset in bold text and subsequently defined/listed (in end-of-chapter resources) in that familiar presentation that students have come to expect.  The one disadvantage is that the explanations are quite succinct, but border on terse sometimes in a manner that might leave weaker students wanting more detailed descriptions in layman's terms to accompany the math jargon.  On the other hand, what the text lacks in depth of prose, it makes up for in breadth of example problems which allows the author to \"show\" the reader how the concepts works rather than \"tell\" him so.   ","consistency_rating":5,"consistency_review":"There were no issues with consistency.","modularity_rating":5,"modularity_review":"Like most statistics textbooks, the topics are presented in such a manner that individual sections or chapters can be omitted freely at the instructor's discretion.  There are occasional references to preceding material (with hyperlinks to another section of the text) which might direct the student to a section the instructor did not cover, but these are infrequent enough as not to be problematic.  One nice feature of this text is that the practice problems and exams are subdivided by section/chapter for easy problem identification which facilitates test construction when sections/chapters have been omitted - this is in contrast to those textbook publishers who simply publish chapter reviews with a jumble of problems the instructor has to sift through when not covering all topics.  ","organization_rating":5,"organization_review":"This textbook is arranged in the typical ordering/grouping of topics as most introductory texts.  Most instructors will find no need to reorder, but this can be easily accomplished if desired.  ","interface_rating":3,"interface_review":"The interface of this textbook is reasonably user-friendly.  Navigation within the textbook sections and supplemental resources is quite straightforward.  The only issue I see here is that the there are no physical copies of statistical tables provided; rather, the reader is directed to \"links to government site tables used in statistics\" - which is a link to a SUNY Polytechnic Institute website with an online textbook (Engineering Statistics Handbook).  The individual 'tables' present at first glance like they might be online distribution calculators, but they are not, and the table values are listed after the content in a form that is not readily conducive to printing.  Arguably, a student could learn to find appropriate values within this page, but scrolling would make this needlessly annoying and the instructor could not provide exam copies of these tables from this site and would need to look elsewhere.  My suggestion is that the book could be improved by directing the students to links to online distributional calculators (for use on HW and in-class) and by providing printer-ready pages (for exams) in the appendices so that both formats were available.","grammatical_rating":5,"grammatical_review":"No obvious issues with grammatical errors.","cultural_rating":5,"cultural_review":"No reason that any reasonable person would find legitimate claim that this book is culturally insensitive.  Statistics is a subject that is universally relevant and the problem sets, descriptions, and examples show no intentional cultural bias or insensitivity.  ","overall_rating":9,"overall_review":null,"created_at":"2020-01-21T13:13:45.000-06:00","updated_at":"2020-01-21T13:13:45.000-06:00"},{"id":3848,"first_name":"Elaine","last_name":"Petrocelli","position":"Adjunct Instructor","institution_name":"North Shore Community College","comprehensiveness_rating":5,"comprehensiveness_review":"This text is comprehensive for an Elementary Statistics course that is not geared toward math or engineering majors.   It covers all the typical topics found in an Intro to Statistics book.   The text includes an introduction and chapter objectives at the beginning of each chapter.   There are examples as well as Try It problems.   At the end of each chapter included are key terms, chapter review, formula review, practice and homework problems and a StatsLab exercise.  Answers to odd questions are available as well.   It includes a nice glossary and index that are easy to use.","accuracy_rating":5,"accuracy_review":"The text is complete and the formulas and key terms are accurate as well as unbiased.   I did not find any errors in the calculations.","relevance_rating":5,"relevance_review":"The content is up to date and will not become obsolete any time soon.   The examples used are classic and ageless.   Because of the structure of the book, any updates would be relatively easy to incorporate.","clarity_rating":5,"clarity_review":"The text is written very clearly in a manner that students can understand.   The examples and try it problems allow the student to apply what they've learned to test their understanding.   The end of the chapter review, key terms and formula review are also very helpful.   The instructions for the problems are clearly written and easy to follow.","consistency_rating":5,"consistency_review":"The text is consistent throughout in format and in usage of industry standard terms and formulas.   The framework and terminology is consistent with that of other published statistics text books.","modularity_rating":4,"modularity_review":"The text can easily be divided into sections that can be taught at different times during the course.       In the preface of the book it even lists alternate sequencing.     There are several sections that could be left out or used as stand alone.","organization_rating":5,"organization_review":"The topics in the book are presented in a clear logical order.   The text includes an introduction and chapter objectives at the beginning of each chapter.   There are examples as well as try it problems.   At the end of each chapter included are key terms, chapter review, formula review, practice and homework problems and a StatsLab exercise.  Answers to odd questions are available as well.    The different color highlighting and bolding also help to transition from topic to topic or to the next chapter.   The organization also allows for skipping sections or teaching out of order.","interface_rating":4,"interface_review":"The interface was easy to use and had no navigation issues.   The images and charts were clear and easy to understand.    The highlighting and bolding made it easy to know when a new section began and easy to find what you were searching for.  I didn't encounter any distortion of images or charts.","grammatical_rating":5,"grammatical_review":"I did not find any grammatical errors.","cultural_rating":4,"cultural_review":"The text appeared to be neutral regarding culture.   There were no offensive or insensitive references.   Examples were inclusive and diverse.","overall_rating":9,"overall_review":"I liked the StatsLab and Try It sections.  I also liked the collaborative exercises and Bringing it Together Homework.     This text offers much opportunity to apply what is learned which is really important in statistics.","created_at":"2020-05-27T20:26:53.000-05:00","updated_at":"2020-05-27T20:26:53.000-05:00"},{"id":3926,"first_name":"Isaias","last_name":"Sarmiento","position":"Assistant Professor","institution_name":"Bunker Hill Community College","comprehensiveness_rating":4,"comprehensiveness_review":"This textbook is a bit different from other textbooks in its coverage of topics. Here are some observations: \r\n1. The topic on ethics is addressed early in the textbook. (Most textbooks I have found don't pay much attention to ethics.)    \r\n2. While there is mention of experiments, I could not find any mention of observational studies. \r\n3. Percentiles are mentioned, but there is no discussion on how to find percentiles methodically. \r\n4. There is strong presence of the use of tree diagrams and Venn diagrams in calculating probabilities. \r\n5. There is strong emphasis on the TI-83/84 to calculate probabilities.","accuracy_rating":4,"accuracy_review":"I did not notice any math computation errors. I did notice some typos. In Section 1.2, there is a math example about the demographics of two colleges in the Spring 2010 quarter, but then there are references to Fall 2007.","relevance_rating":4,"relevance_review":"I'm reviewing the 2018 edition of the textbook. Some of the contexts seem a little outdated. (In Chapter 8, there is an example about smartphones, and the phones listed date back to the early 2010s.) With that said, I don't think the outdated contexts detract too much from the content. At least they are still within the same decade!","clarity_rating":4,"clarity_review":"The textbook sufficiently defined vocabulary terms and, where appropriate, provided examples of those terms. \r\n\r\nIn Chapter 3, there is mention of the P(A and B) probability. But I think we have to be careful about this notation. If the problem involves a single selection, then P(A and B) is really just a joint probability -- one fraction, that's it. But if the problem involves two selections (with or without replacement), now we're talking about the multiplication rule. The book mentions the multiplication rule early on in 3.2, but I just couldn't find any examples of how with/without replacement is applied within the multiplication rule. \r\n\r\nThe discussion on conditional probability could have included the intuitive approach.","consistency_rating":4,"consistency_review":"It seemed that the terminology used was consistent throughout the textbook. The one time where I felt that there was an inconsistency is in the construction of histograms. In some histograms, the classes overlapped (e.g. 59.95 - 61.95, 61.95 - 63.95). In other histograms, the classes did not overlap. Also, some histograms used class boundaries (Example 2.8), while other histograms did not (Example 2.9). On page 82, the authors state that there is more than one way to create a histogram. However, I feel that the authors should stick with just one way for consistency.","modularity_rating":5,"modularity_review":"The textbook does a good job in breaking down each section through Examples, a Try It! feature, Collaborative Exercises, and a Statistics Lab. Some sections discuss how to use a TI-83/84 calculator to obtain answers. At the end of each chapter, there is a Key Terms list, a Chapter Review, and a list of math exercises followed by the solution key.","organization_rating":3,"organization_review":"Overall, the topics are presented logically. There were some instances in which I felt that specific vocabulary terms were introduced a little early. For example, the term \"probability\" was defined in Chapter 1, but only in Chapter 3 was the term fully addressed. The concept of sampling with or without replacement was described in Section 1.2, when its relevance was really in Chapter 3. The term \"median\" was mentioned in Section 2.3 as part of the larger discussion of the percentiles, but then it was formally defined in Section 2.5 as an example of a measure of central tendency. I felt that the discussion on box plots in 2.4 should have been integrated with the discussion on quartiles in 2.3. The linear regression equation was mentioned before the linear correlation coefficient, which I found unusual. \r\n\r\nOne recommendation would be to place vocabulary terms in boxes. The terms were bold-faced, but the text can sometimes be so dense that vocabulary boxes would have been helpful in breaking up the text. \r\n\r\nThe page breaks in some places seem strange. On page 138, halfway through the page, there is an instruction to find the standard deviation, but the rest of the page is blank. On page 141, there is only one line of text.","interface_rating":5,"interface_review":"The interface was sufficiently clear. I noticed that, in the online version of the textbook, the exercises that referenced tables and figures included a hyperlink to the table/figure so that the student can easily refer to it. Also, the online version allows you to highlight text and make comments, as though you were writing notes within the book.","grammatical_rating":4,"grammatical_review":"In a couple of instances did I find a grammar or spelling error. In the 1.10 Try It!, the graph should say \"per Student\", not \"per Students\". On page 181, the word \"rolls\", as in \"rolls of a fair die\", was misspelled as \"roles\".","cultural_rating":5,"cultural_review":"The textbook was culturally sensitive. The book made an effort to use names that imply different racial/ethnic backgrounds (e.g. Rosa, Binh). The textbook was also willing to include applications that may be deemed controversial (e.g. AIDS). I did notice that, at least in the first chapter, there seemed to be a focus on California-related contexts, though I don't recall the entire textbook being that way.","overall_rating":8,"overall_review":"If you are accustomed to using a author like Triola, this textbook might take some getting used to. You will be hard pressed to find any mention of the counting methods (factorial, permutation, combination), and this may help explain why the binomial probability distribution formula is not mentioned. Regarding hypothesis testing, the null hypothesis is not restricted to the \"equal\" case, as it considers the cases \"less than or equal to\" and \"greater than or equal to\". With its focus on the TI-83/84, the textbook effectively avoids other accessible tools like Excel and even normal probability tables. If you have students who do not have access to a TI-83/84, then you will need to provide extra instruction.","created_at":"2020-06-07T22:22:58.000-05:00","updated_at":"2020-06-07T22:22:58.000-05:00"},{"id":5137,"first_name":"Tingting","last_name":"Fang","position":"Associate Professor","institution_name":"North Shore Community College","comprehensiveness_rating":5,"comprehensiveness_review":"This OER book covers all the required topics as an introductory statistics text. The content is well presented using examples, lots of exercises problems. After examples, there are Try it questions provided. This gives the students chance to check their understandings of the topics immediately. TI calculators are widely used in this text, so some formulas or complicated mathematical theories are not introduced. For Non-math majors, I would say this is good and give the students chance to focus on the application part of the theory. TI-calculator command descriptions are included within examples. Students can easily follow what is taught.","accuracy_rating":5,"accuracy_review":"Most of the contents are accurate and presented very well.","relevance_rating":5,"relevance_review":"Content is up-to-date, but not in a way that will quickly make the text obsolete within a short period of time. The text is written and/or arranged in such a way that necessary updates will be relatively easy and straightforward to implement.","clarity_rating":4,"clarity_review":"It is easy for me as an instructor to read the book since I already know the fundamental concepts for probabilities and statistics. However, there are some symbols that are not commonly used in the other same level statistics book. For example, chapter 10 presents how to calculate confidence interval. EBM is used to represent” margin of error”. This 3-word symbol is not user friendly in the formulas. It is better to use a single letter E to denote it as in the other books","consistency_rating":5,"consistency_review":"It is very consistent. The language of the contents is easy to follow.","modularity_rating":4,"modularity_review":"In general, each model of the book is well designed. Different sections could be rearranged easily depending on the topics covered by the instructors. One thing that can be improved is in chapter 2: Descriptive Statistics. Measures of the Location (2.3) is introduced before Measures of the center (2.5). However, the concept of mean (average) is used when Percentile is calculated in sec 2.3. I would suggest to move sec 2.5 before sec 2.3.","organization_rating":5,"organization_review":"This book is well organized. The part I like most is that each chapter includes contents part, Key terms, Chapter review, homework problems and solution keys. Students can easily find what they need. It is easy to use.","interface_rating":5,"interface_review":"It is very easy to find the right contents.","grammatical_rating":5,"grammatical_review":"It is well written. It is easy to understand what the book is trying to present.","cultural_rating":5,"cultural_review":"The text is not culturally insensitive or offensive in any way.","overall_rating":10,"overall_review":"As an OER book, this text is a good choice with no cost. For those who heavily rely on TI-calculators, this book is even better.","created_at":"2021-06-23T12:51:18.000-05:00","updated_at":"2021-06-23T12:51:18.000-05:00"},{"id":5142,"first_name":"Stanley","last_name":"Elias","position":"Adjunct Professor","institution_name":"Massasoit Community College","comprehensiveness_rating":5,"comprehensiveness_review":"Quite comprehensive as an introductory text for non-technical students. It touches on topics not usually seen in an introductory text (hypergeometric and Poisson distributions, e.g.) The index is an effective search tool for finding specific topics. New terms are generally introduced at the beginnings of the chapters.","accuracy_rating":4,"accuracy_review":"I noticed a very few minor inconsistencies in the tables, but on the whole the text is accurate and unbiased.","relevance_rating":5,"relevance_review":"Content is in keeping with current society and technology and can be easily updated when the need arises. The modularity of the text allows for the easy rearrangement of the order of presentation.","clarity_rating":5,"clarity_review":"It is easy for mathematics texts to lapse into jargon. That is not the case here. Topics are explained carefully and logically in a way that is easy to follow. The conclusions thus reached are abundantly clear.","consistency_rating":5,"consistency_review":"The terminology used in the text is consistent from one chapter to the next. Especially appealing are the \"Try It\" problems that follow example problems, enabling the student to apply what was illustrated in the example","modularity_rating":5,"modularity_review":"Each chapter follows from the one before and leads to the next, but if desired they can be rearranged without any loss in continuity. For example, I prefer to teach correlation and regression earlier in the course than it usually occurs, so I present Chapter 12 (Linear Regression and Correlation) between Chapter 3 (Probability Topics) and Chapter 4 (Discrete Random Variables). This change is mentioned in the preface as a possible rearrangement.","organization_rating":5,"organization_review":"Topics are presented in the logical order one would expect. I especially appreciated the different problem sets (Practice, Homework and Bringing It Together) that present problems of increasing difficulty.","interface_rating":5,"interface_review":"There are no interface issues. The charts and tables are appropriately sized and colored and easy to read.","grammatical_rating":5,"grammatical_review":"I found no grammatical errors.","cultural_rating":5,"cultural_review":"The text is apolitical. Some of the names mentioned in the problems appear to be the only cultural or ethnic references.","overall_rating":10,"overall_review":"I have used this text the last three times I have taught the course, and I intend to use it again. I especially appreciate the inclusion of Texas Instruments calculators when appropriate. The guidelines and step-by-step procedures are a great help. Another help is the set of practice tests and finals in Appendix B. The text is not as slickly produced as those from the major publishers, but it is still complete and very accessible to students. And as an Open Source text, there is never any excuse not to have a copy!","created_at":"2021-06-24T13:44:31.000-05:00","updated_at":"2021-06-24T13:44:31.000-05:00"},{"id":33408,"first_name":"Emily","last_name":"Breit","position":"Professor","institution_name":"Fort Hays State University","comprehensiveness_rating":4,"comprehensiveness_review":"The textbook covers the chapters you would generally find in a one semester statistics course.  It provides general coverage of the content areas including: descriptive statistics, probability, CLT, confidence intervals, hypothesis testing, and linear regression.","accuracy_rating":5,"accuracy_review":"Content appears to be error-free and unbiased.","relevance_rating":5,"relevance_review":"The content is up-to-date and, as with most statistics textbook, the material should remain relevant for an extended period of time.","clarity_rating":4,"clarity_review":"The textbook provided simple, easy to follow examples.","consistency_rating":4,"consistency_review":"Terminology and variables were consistent throughout the text.","modularity_rating":5,"modularity_review":"The authors did a good job of providing both written and visual examples of the content.","organization_rating":4,"organization_review":"The chapters followed from descriptive statistics and probability into more application based examples.","interface_rating":4,"interface_review":"Charts and graphs were clear and provided additional insight into the problems presented.","grammatical_rating":5,"grammatical_review":"Grammatical errors were not detected.","cultural_rating":5,"cultural_review":"The examples were easy to follow and were based on content that is inclusive to students with diverse backgrounds.","overall_rating":9,"overall_review":null,"created_at":"2021-10-13T14:17:12.000-05:00","updated_at":"2021-10-13T14:17:12.000-05:00"},{"id":33661,"first_name":"Matthew","last_name":"van den Berg","position":"Professorial lecturer","institution_name":"American University","comprehensiveness_rating":5,"comprehensiveness_review":"Provides coverage of all the usual topics for an introductory statistics course along with extra topics that many courses will likely skip due to time constraints.","accuracy_rating":5,"accuracy_review":"I came across no errors or accuracy issues, and did not perceive any biases.","relevance_rating":5,"relevance_review":"The text is relevant and up-to-date.  It's introductory statistics, so I can't really imagine a text being \"out-of-date\" in this field.  The one issue here may be that this text provides additional instruction for using a TI-83+ and/or TI-84 calculator.  This may still be the preferred calculator for many students, but students many students may only rely on computer based analysis so the calculator instructions are less valuable.","clarity_rating":5,"clarity_review":"The text is well written and comparable to the clarity of any other statistics textbook.  This may be subject to students' preferred learning methods however, as this text heavily emphasizes examples to explain new concepts.  Often rather than introducing the theory behind a new concept, then providing an example, the text often goes straight into an example and uses that example to show the theory.","consistency_rating":5,"consistency_review":"The formulas and language are consistent throughout.","modularity_rating":5,"modularity_review":"I skipped several sections within the text, and the flow of the material and explanations did not suffer from it.","organization_rating":4,"organization_review":"Sometimes, the text over-uses examples as an introductory tool for new concepts.  This may be helpful for some students, while other students may prefer an organization structure the first provides theory and formulas, and then offers an example.  I think the heavy use of examples in the text is generally a good thing, however it can lead to formulas and theoretical concepts getting somewhat lost in those examples.","interface_rating":5,"interface_review":"I experienced no interface issues with the text.","grammatical_rating":5,"grammatical_review":"The text was well-written and free of grammatical errors.","cultural_rating":5,"cultural_review":"I noticed no cultural biases or insensitivity issues.","overall_rating":10,"overall_review":"I was happy with the textbook for an introductory statistics course that covered: descriptive statistics, probability, hypothesis testing, and simple linear regression.  Stylistically, the text relies heavily on examples to explain the concepts.  This provides a lot of chances for students to read applied examples, but can sometimes obscure the core concepts, theories, and formulas.","created_at":"2022-01-14T10:01:50.000-06:00","updated_at":"2022-01-14T10:01:50.000-06:00"},{"id":33793,"first_name":"Lance","last_name":"Kruse","position":"Adjunct Assistant Professor","institution_name":"Bowling Green State University","comprehensiveness_rating":5,"comprehensiveness_review":"The textbook addresses the foundational concepts for statistics, including a robust discussion of sampling and descriptive statistics. Even for students who may not frequently utilize inferential statistics, the beginning chapters provide a wealth of knowledge about descriptive statistics and introductory probability concepts. The inferential statistics are quite comprehensive and organized logically based on the samples and means being compared. The concepts align with the several introductory educational statistics courses I have taught.","accuracy_rating":5,"accuracy_review":"No errors or biases were identified.","relevance_rating":5,"relevance_review":"The topics used in the examples span a diverse range of topics including higher education enrollment, high school sports, technology, research projects, business, politics, health care, and many everyday life examples (e.g., pizza delivery). Some of the dates mentioned in the scenarios are a bit dated (e.g., year 2008, iPhone 4s), but these do not impact the purpose of the example. Statistics do not become out of date, so there is not a concern about the relevancy of the content moving forward. The textbook does provide support for using a TI-83/84 calculator, which is quite nice to improve accessibility to the calculations required.","clarity_rating":5,"clarity_review":"The writing is clear, accessible, and approachable to any reader regardless of their prior statistics knowledge and/or experience.","consistency_rating":5,"consistency_review":"Terminology is clear and consistent. There are helpful glossaries at the end of each chapter to define the key terms used. Parenthetical clarifications are provided to ensure ideas are clear.","modularity_rating":4,"modularity_review":"Each section has several subheadings to more clearly identify specific sections of the reading. Those sections are accessible as separate standalone readings that do not require readings of previous sections to understand them. The text uses several examples to clarify the concepts and does not overly refer to previous sections of the text.","organization_rating":5,"organization_review":"The flow of topics is logical and appropriate for an introductory statistics course.","interface_rating":5,"interface_review":"The PDF download is neat and clear. There is a digital table of contents that shows all of the chapters and subsections in the chapters that automatically navigate you to those sections. This makes it very easy to jump around to various parts of text with ease.","grammatical_rating":5,"grammatical_review":"No grammatical errors were noticed.","cultural_rating":3,"cultural_review":"Gender is presented as a binary (male/female) and is not inclusive of the full spectrum of gender identity. However, this issue is not relegated to only this text and is commonly present in most statistics textbooks. I believe a standalone discussion of inclusivity in research and statistics should be presented by the instructor to discuss the importance of inclusivity in research, but yet the practical issues this may cause for statistics (e.g., having inclusive categories for self-identification that may result in very small sample sizes that violate the statistical assumptions required for an inferential test). These discussions should be happening in the classroom to ensure students are engaging in ethical and culturally responsive research while also understanding the implications of such decisions.","overall_rating":9,"overall_review":null,"created_at":"2022-04-17T12:29:35.000-05:00","updated_at":"2022-04-17T12:29:35.000-05:00"},{"id":33840,"first_name":"Aaron","last_name":"Zerhusen","position":"Assistant Professor","institution_name":"Dominican University","comprehensiveness_rating":5,"comprehensiveness_review":"Most of the typical topics covered in an Introduction to Statistics class are all covered in reasonable detail.  Basic descriptive statistics, constructing and reading various types of graphs and charts, an introduction to relevant concepts of probability, and hypotheses testing.   Notably, Bayes’ Rule is absent.  Instructions for use of a TI-83/84 calculator are included, but no other technology is used.  The data sets used in the text (including within the homework) do not seem to be provided anywhere in a format that would allow for easy use of technology such as Excel, Minitab, or R.  The inclusion of a section on ethics in statistics and experimental design in the first chapter is a welcome feature.","accuracy_rating":5,"accuracy_review":"The content is accurate.","relevance_rating":4,"relevance_review":"Material is presented with some examples drawn from real-world data, but there could be more.  Again, examples and homework problems utilizing data sets that are provided in a format (such as csv files) that could be read by a variety of statistics software would help greatly.","clarity_rating":3,"clarity_review":"The clarity of the exposition within the sections is lacking.  Explanations are terse, relying on the examples to illustrate the concepts.  Definitions and theorems are not clearly indicated, but rather are often hidden within a paragraph.  The key terms, chapter review, and formula review sections at the end of each chapter are helpful.","consistency_rating":5,"consistency_review":"The notation and techniques introduces are consistent.","modularity_rating":5,"modularity_review":"The modularity by chapter is typical of a book of this type.  A flowchart of dependencies would help instructors, and is not provided.","organization_rating":5,"organization_review":"The organization is typical of an introduction to statistics text.","interface_rating":5,"interface_review":"The interface is standard and clear.  The web version of the book takes advantage of HTML to show/hide solutions as appropriate in exercises for students to work through.","grammatical_rating":3,"grammatical_review":"There are a number of errors in the mathematical typesetting which detract from the clarity of the book.","cultural_rating":5,"cultural_review":"Examples are pulled from data for a range of subjects.  The language used in the text is rather neutral.","overall_rating":9,"overall_review":"If the instructor is careful to address the places where the book is not clear I think this will be a fine textbook.  The inclass activities and lab assignments are very nice.","created_at":"2022-05-09T12:40:03.000-05:00","updated_at":"2022-05-09T12:40:03.000-05:00"},{"id":33987,"first_name":"Nels","last_name":"Grevstad","position":"Professor of Statistics","institution_name":"Metropolitan State University of Denver","comprehensiveness_rating":3,"comprehensiveness_review":"The book covers all the topics typically covered in an introductory statistics class, but the depth of the coverage is sometimes less than adequate.  As an example, self-selected samples are described as \"unreliable\", but there's no mention of WHY.  As another example, there book provides almost no intuition behind the (probability) Multiplication Rule and Addition Rule.","accuracy_rating":3,"accuracy_review":"The content is generally accurate, but in a few places it's just plain wrong.  For example, Figs. 8.2 and 8.3 attempt to explain confidence intervals using a graph of a normal curve centered on X-bar (the SAMPLE mean) and with the CONFIDENCE INTERVAL endpoints marked on the horizontal axis capturing the middle 90% of the normal distribution.  What variable is this the distribution of?","relevance_rating":3,"relevance_review":"Some of the data sets will become outdated with time, but I think that's true of any statistics textbook.","clarity_rating":3,"clarity_review":"The clarity of the book is generally adequate, but explanations are often lacking, and there are numerous places where clarity could be improved upon.  An example of this is using the same symbol to represent different things -- in Try It 3.13 (a probability problem), the letter S is used to represent an event, but everywhere else in the chapter, S is used to represent the sample space.","consistency_rating":3,"consistency_review":"The text is generally internally consistent, but there are several inconsistencies. For example, in Chapter 2, sometimes the symbol used for the sample standard deviation is Sx (S with subscript x), other times it's just S (no subscript).  As another example, sometimes the right side of the (probability) Multiplication Rule is written as P(B)P(A|B) and other times as P(A|B)P(B).","modularity_rating":4,"modularity_review":"There are not any major problems with the modularity of the book that I could see.","organization_rating":2,"organization_review":"The organization/structure/flow of the book is NOT well-thought-out.  \r\n\r\nThere are numerous places where a term is used before it has been defined.  For example, in Example 1.3 the term \"simple random sample\" is used before that term has even been defined. In Try It 1.10, a histogram is used before histograms have even been covered.\r\n\r\nFurthermore, there are several instances where NEW ideas are introduced in the Chapter Review section.  An example of this is describing the relative advantages and disadvantages of stem-and-leaf plots versus histograms in the Chapter 2 Review, but this isn't mentioned at all in the main body of the chapter.  Another example of this (also in the Chapter 2 Review) is the introduction of grouped bar charts and stacked bar charts, neither of which is discussed in the main body of the chapter.\r\n\r\nThere are many other organizational deficiencies, too numerous to mention here.","interface_rating":4,"interface_review":"I only saw only a few minor issues with the interface of the book, and they shouldn't distract or confuse the reader.","grammatical_rating":2,"grammatical_review":"There are grammatical errors and typos, and in some cases, they can cause confusion.  For example, the term \"statistic of a sampling distribution\" appears in multiple places (it's supposed to be \"sampling distribution of a statistic\"), including in a section header.","cultural_rating":4,"cultural_review":"The text is not culturally insensitive or offensive, but it does not appear to me that the authors went out of their way to find examples that are particularly inclusive.","overall_rating":6,"overall_review":"I do not plan on using this book for my classes in future semesters.","created_at":"2022-08-18T12:02:06.000-05:00","updated_at":"2022-08-18T12:02:06.000-05:00"},{"id":34058,"first_name":"Lauren","last_name":"Farr","position":"Instructor of Mathematics","institution_name":"Spartanburg Community College","comprehensiveness_rating":5,"comprehensiveness_review":"In reviewing this material, it appears as though the text meets or exceeds the standards set for traditional textbooks for an Introductory Statistics course.  The content appears to be comprehensive, accurate, and up to date.  This text could be used to teach an Elementary Statistics class and covers enough topics that it could be used for an additional course in Intermediate Statistics.","accuracy_rating":5,"accuracy_review":"I have yet to find an error in any of the material.","relevance_rating":5,"relevance_review":"The problems in the book are made in such a way that the text will not become obsolete.  For example, they use general topics such as heights of people on a sport’s team instead of naming a specific team or year.   This is good because the book can be used for a longer period of time.","clarity_rating":5,"clarity_review":"The book gives the formal definitions and applicable theorems.  For clarity, it then gives problems and examples to illustrate what these definitions and theorems actually mean so students can better understand them.  The examples are provide students with a reasoning behind why we \"need\" the theorems to begin with and how Statistics can apply to their life.","consistency_rating":5,"consistency_review":"Material is presented in an orderly way.  It gives the definition and applicable theorems.  It then gives problems and examples to illustrate what these definitions and theorems actually mean so students can better understand them.","modularity_rating":5,"modularity_review":"The glossary and the table of contents are especially important aspects of online learning tools.  This text makes it extremely easy to switch between different topics and navigate around the book.  The book is broken up into sections that cover a specific topic, so it is easy to find material.  This divides the material into smaller sections which helps students better learn the material and to not become overwhelmed.","organization_rating":5,"organization_review":"The glossary and the table of contents are especially important aspects of online learning tools.  This text makes it extremely easy to switch between different topics and navigate around the book.  The book does go in a logical fashion from basic Statistics concepts/definitions to more complex ones.","interface_rating":5,"interface_review":"Many students do not want to write in a physical textbook.  This online book allows you to highlight sections and make notes while you are reading that you can easy access later without having to flip through the book to look for where you wrote notes.  I have yet to find any interface issues.","grammatical_rating":5,"grammatical_review":"I have yet to find any grammatical errors.","cultural_rating":3,"cultural_review":"The text is not culturally insensitive as most problems are about “people” or “doctors” or “neighbors”.  There is no reference to race, ethnicities, or backgrounds.","overall_rating":10,"overall_review":"This appears to be a fabulous textbook.  I look forward to investigating it further.  I am also excited to apply some of the ideas, such as the group project problems, to my classes.","created_at":"2022-09-22T09:34:45.000-05:00","updated_at":"2022-09-22T09:34:45.000-05:00"},{"id":34255,"first_name":"Kim","last_name":"Proctor","position":"Lecturer","institution_name":"California State University, Dominguez Hills","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers multiple areas that are necessary for students to grasp a basic knowledge of statistics. However, I would have liked to see the inclusion of information for some kind of computer-assisted analysis of descriptive statistics, contingency tables, z-test, t-tests, ANOVA, linear regression, and chi-square. Whether these analyses were conducted via excel, SPSS, some free online calculator, or R, these would have been helpful as I end up using other resources in order to include computer-assisted analyses to familiarize my students with these processes.   The index is comprehensive. However, some information included in both the main sections and glossary is somewhat confusing, e.g., the data set(s), of which there are only two, are not fully explained and are somewhat unuseful for multiple forms of analysis practice.","accuracy_rating":5,"accuracy_review":"I did not notice any errors in the accuracy of the book. However, the supplemental materials--in particular the lecture slides had a few slight errors.","relevance_rating":3,"relevance_review":"While I do believe the book has excellent longevity, I maintain that adding support information on computer-aided analyses for each of the sections using Excel, SPSS, R, or some free online calculator would make the book much more relevant and more attractive to instructors who would prefer a book that includes such information. I do believe the way the book is arranged and formatted aids in ease of updating. With that stated, some questions discuss elections, polling or other issues that do not account for the current influence and uses of social media, the internet, and smart phones.","clarity_rating":2,"clarity_review":"The text is somewhat accessible. I do not believe the way the different areas of text, examples, and explanations are set up within the book are as accessible, clear, and readable as they could be. In fact, the format of the text and examples at times makes the book difficult to follow. As stated in a previous section, some information included in both the main sections and glossary is somewhat confusing, e.g., formulas, concepts, and the data set(s)(of which there are only two) are not fully explained and are somewhat unuseful or confusing without further explanation from the instructor and examples from other texts, this is particularly relevant to the \"try this, and \"let's practice\" examples.","consistency_rating":5,"consistency_review":"The text is extremely consistent in terms of terminology and framework. Although, in my opinion, the terminology and framework are not as accessible to college-level intro stats students as it could be.","modularity_rating":5,"modularity_review":"I believe the modularity of the reading sections and the inclusion of a course pack that can be uploaded to Canvas or Blackboard is extremely helpful. I can assign students to read only one or two sections of a chapter, and I can mix and match sections from different chapters. I absolutely love the Modularity of this book.","organization_rating":3,"organization_review":"The topics are presented in a logical and clear fashion. However, I believe the ordering of topics could be improved. For example, ANOVA should be presented after the chapter on 2-sample t-tests, and Normal Distribution should be presented after the chapter on probability.","interface_rating":4,"interface_review":"The text is free from navigation issues and distortion of images. However, the images and other display features are not that aesthetically pleasing: most are presented as grey tables, etc.","grammatical_rating":5,"grammatical_review":"I noted no grammatical errors in the text.","cultural_rating":2,"cultural_review":"The text is not culturally offensive. However, the text is extremely insensitive. It does not account for alternative options for male/ female, and is not inclusive towards varied cultures and beliefs. Racial \"minorities\" are rarely mentioned in the text, and are not reflected in visuals.","overall_rating":8,"overall_review":"1. I suggest alterations/ additions to the information in the text: in the form of some kind of computer-assisted analysis of descriptive statistics, contingency tables, z-test, t-tests, ANOVA, linear regression, and chi-square. \r\n2. I do not believe the way the different areas of text, examples, and explanations are set up within the book are as accessible, clear, and readable as they could be. In fact, the format of the text and examples at times makes the book difficult to follow. \r\n3. With regard to relevance, some questions discuss elections, polling, or other issues that do not account for the current influence and uses of social media, the internet, and smartphones. \r\n4. The text is not culturally offensive, but it is extremely insensitive. It does not account for alternative options for male/ female, and is not inclusive towards varied cultures and beliefs. Racial \"minorities\" are rarely mentioned in the text and are not reflected in visuals.","created_at":"2022-12-08T22:00:37.000-06:00","updated_at":"2022-12-08T22:00:37.000-06:00"},{"id":34706,"first_name":"Daniel","last_name":"McGough","position":"Graduate Student Instructor","institution_name":"Purdue University","comprehensiveness_rating":4,"comprehensiveness_review":"This book covers a broad category of statistics and statistical techniques, some of which I just ended up skipping.","accuracy_rating":5,"accuracy_review":"This book is very accurate.","relevance_rating":3,"relevance_review":"As an instructor in a psychology department, there were a lot of things in this text that I didn't end up needing or using.","clarity_rating":4,"clarity_review":"I think some of the terminology, while accurate, was difficult for some of my students to understand.","consistency_rating":5,"consistency_review":"Good internal consistency in terminology and formulas.","modularity_rating":4,"modularity_review":"Pretty good modularity, as i only assigned part of each chapter for readings.","organization_rating":5,"organization_review":"I think the organization is great. It starts off with the background things one needs, such as what a random variable is and what distributions are, then advances through more complex information regarding inferential statistics. I might change the order of a few of the chapters towards the end of the book, but that would be all.","interface_rating":4,"interface_review":"There are a lot of \"Box\"es that almost seem necessary for students to read/interact with to get the knowledge in them. I would just make those part of the plain text.","grammatical_rating":5,"grammatical_review":"No grammar errors that I caught.","cultural_rating":5,"cultural_review":"I don't think it referred to race at all.","overall_rating":9,"overall_review":"This book is a great resource for teaching intro stats. However, I do think that the next time I teach this material, I will be switching to Learning Statistics with R or one of its variants. That is not because I think this textbook is bad by any means, but it actually is just too general in its approach. I want an open text book that is more geared towards psychology students, rather than general statistical use.","created_at":"2023-10-26T14:27:06.000-05:00","updated_at":"2023-10-26T14:27:06.000-05:00"},{"id":34838,"first_name":"Amish","last_name":"Mishra","position":"Assistant Professor","institution_name":"Taylor University","comprehensiveness_rating":5,"comprehensiveness_review":"The text provides the necessary details of the most important topics in an introductory statistics course without going too deep into details or calculations.","accuracy_rating":5,"accuracy_review":"Formula 10 in Appendix F has the bounds flipped on the gamma function’s integral. It should go from 0 to infinity.","relevance_rating":3,"relevance_review":"Perhaps using the TI calculators is now a thing of the past. I can understand if the authors would like to keep the statistical concepts in the focus rather than the tool, but today statistics can hardly be done in the workplace or academia without software like R or SPSS.","clarity_rating":5,"clarity_review":"I like the dotplot introduction to give students an easy visualization and invitation to statistics","consistency_rating":5,"consistency_review":"I found the section at the end listing the mathematical notation to be quite a helpful reference","modularity_rating":5,"modularity_review":"It has a similar format to most statistics textbooks I’ve seen. Perhaps the chapter on descriptive statistics could be broken down further into a graphical chapter and a numerical chapter.","organization_rating":5,"organization_review":"The text has clear organization and supplements new concepts with good examples","interface_rating":5,"interface_review":"I found it quite nice to have the book in pdf or online format. The various formats are helpful for different students’ learning styles","grammatical_rating":5,"grammatical_review":"I did not see any","cultural_rating":5,"cultural_review":"examples were great","overall_rating":10,"overall_review":"-\tIn the descriptive statistics section, it could also include examples of heatmaps and pictographs because those have become very popular\n-\tIn the section about exponential distributions, some more justification can be provided for the memoryless property. For example, this sentence made me question the utility of the distribution: “In this case it means that an old part is not any more likely to break down at any particular time than a brand new part.” It is unintuitive for students to think this so some justification is needed for why thinking like this makes sense.\n-\tIntroduction of Chapter 6: In reference to the normal distribution, the authors said, “The probability density function is a rather complicated function.” I would rather say it is surprisingly elegant so students also gain an appreciation for its formulation 😊\n-\tKey terms section at the end of Chapter 7: not sure why there’s a paragraph for exponential distributions again when they were already discussed in 5.3\n-\tIn chapter 11, it may be worth commenting briefly on how the chi-squared test of independence is related to the chi-squared test of association\n-\tOverall, a fantastic resource that is open and free for anyone who wants to self-study statistics well. Thank you!","created_at":"2024-01-03T08:46:02.000-06:00","updated_at":"2024-01-03T08:46:02.000-06:00"},{"id":34985,"first_name":"Ivan","last_name":"Temesvari","position":"Instructor","institution_name":"Northeastern Illinois University","comprehensiveness_rating":4,"comprehensiveness_review":"The text covers the topics of what any other introductory statistics text would cover. The example problems throughout the chapters may not be fancy, but still get the job done with well-organized and formatted tables and figures which appear to have been created using a graphics calculator. Each chapter is robust with exercises, try-it problems for the student to stop and practice/reflect on the content, a chapter review, homework problems, and solutions to the practice problems. There is an entire chapter dedicated to use of a TI-83 or TI-84 calculator with detailed instructions. The index of the text is well organized, and it is recommended to use the book in web format due to the highlighting tool available.","accuracy_rating":5,"accuracy_review":"I did not encounter any staggering errata in my review of the text. However, I did not read every word and cross check every exercise and solution. I'd imagine errata would be addressed periodically as the text has been updated to a 2nd edition. Also, the main page of the text has an errata page dedicated to errors found and it is currently active as I see a dated submission of the same day I happen to be writing this review 4/4/2024.","relevance_rating":5,"relevance_review":"Every chapter contains exercise problems that are based on real-life examples which shows a good attention to detail in how the topics are delivered. The mathematical symbols and typesetting are clear and match up with any advanced mathematical text of known importance. In fact, since this text incorporates the use of current technology (e.g., TI-84+ calculator), in some ways it is better than a more formal stats text.","clarity_rating":4,"clarity_review":"Some statistical concepts require the use of current technology for access to graphical figures which help support the understanding of various topics throughout the text.","consistency_rating":3,"consistency_review":"I didn't like how some of the sections go straight into a Stats Lab problem without any buildup or introduction to the relation of the problem to the topics covered in the associated chapter (e.g. 8.4 Confidence Interval (Home Costs)).","modularity_rating":5,"modularity_review":"This text is very well organized. As I mentioned, every chapter has many sections of independent topics along with sections dedicated to Practice Problems, Homework, and even Solutions to the Practice Problems. There is even a section dedicated to References which is good to have in case you wanted to find out where some of the data was collected from, but also to delve more into the data from its source.","organization_rating":3,"organization_review":"I didn't like how some of the sections go straight into a Stats Lab problem without any buildup or introduction to the relation of the problem to the topics covered in the associated chapter (e.g. 8.4 Confidence Interval (Home Costs)). Otherwise, every chapter is delivered in the same fashion.","interface_rating":5,"interface_review":"The web-based text utilizes a Highlighting feature which allows an account holder access to their previously highlighted text for a quick review of their notes. I personally would find this very useful as I prefer to highlight text as I read it for a note later. The highlight feature also allows a few different colors and a separate web page to review all of the highlighted text in one place instead of having to scroll and click around the entire text.\r\nAs I mentioned before, it's best to read the book in web form, so that could be a draw back if you were using the pdf form. However, the pdf form has all of the same content as the web based form. Personally, I prefer the pdf form if I want to scroll through the pages of the chapter instead of having to click next repeatedly as I scan through the sections of the text.","grammatical_rating":5,"grammatical_review":"I found that the text to be well written (in English).","cultural_rating":5,"cultural_review":"It's a statistics text with many varied examples across a plethora of relatable topics which allow for the discovery of statistical methods. I found the examples related to food or athletics to be most interesting.","overall_rating":9,"overall_review":"These OpenStax textbooks now have Instructor and Student Resources to supplement the experience. Also, there are now Technology Partners that have developed their own content to supplement the text with auto graded assignments and LMS interfaces.","created_at":"2024-04-04T21:48:41.000-05:00","updated_at":"2024-04-04T21:48:41.000-05:00"},{"id":35770,"first_name":"Karen","last_name":"Roemer","position":"Professor","institution_name":"Central Washington University","comprehensiveness_rating":4,"comprehensiveness_review":"The chapters are well structured and offer key terms and multiple reviews at the end of each chapter. The organization of practice examples throughout the book is great. I wish they had more data sets, data sets for download as excel or text files. They could also provide links to open data bases with more sample data sets","accuracy_rating":4,"accuracy_review":"The information provided seems accurate. The hypothesis testing chapters are limited to group differences/mean values. They should add information on hypothesis testing for relationships/regression coefficients.","relevance_rating":5,"relevance_review":"it seems that the content gets updated frequently and stays current.","clarity_rating":4,"clarity_review":"The content is written very succinct. Sometimes a little more context would be helpful","consistency_rating":4,"consistency_review":"very clear and consistent framework throughout the book","modularity_rating":4,"modularity_review":"clear structure, each chapter has the same main components, so it is easy to find content","organization_rating":4,"organization_review":"the table of contents frame makes it easy to navigate","interface_rating":5,"interface_review":"very intuitive for me to use and navigate the book","grammatical_rating":4,"grammatical_review":"I did not see any issues with the writing style or grammar. My students gave overall good feedback regarding the textbook in my class.","cultural_rating":3,"cultural_review":"it seems very neutral.","overall_rating":8,"overall_review":"This is a great textbook for teaching the main concepts of inferential statistics. It is vary math oriented and if you want to use it for your class, you need to come up with you own applications, data sets, and applied examples for your target population.","created_at":"2026-02-09T12:18:06.000-06:00","updated_at":"2026-02-09T12:18:06.000-06:00"},{"id":35777,"first_name":"Sudipta","last_name":"Mallik","position":"Assistant Professor","institution_name":"Marshall University","comprehensiveness_rating":4,"comprehensiveness_review":"Standard topics of an introductory statistics textbook are covered. Some sections can be expanded. For example,  Section 4.3 Binomial Distribution. There are no detailed explanations for binomial coefficients, factorials, and the formula for P(X=k). I heard this specific complaint regarding Binomial Distribution from multiple professors. The authors should seriously consider rewriting this section.","accuracy_rating":5,"accuracy_review":"I did not find any significant errors yet. A minor correction I would suggest: When X is a random variable, writing P(x\u003e3) is incorrect (see page 241). It should be  P(X\u003e3).","relevance_rating":5,"relevance_review":"I appreciate the examples regarding students/education, profits/economics, diseases/health sciences, technology. Some data from government websites can be used/cited. The authors should consider providing R or Python codes besides TI84 instructions to be more relevant.","clarity_rating":4,"clarity_review":"The style of writing focuses on \"what a concept does\" and \"how it can be used\" which is good for a first course of statistics. I would suggest emphasis also on providing formal definitions and statement of theorems before or after discussing more.","consistency_rating":5,"consistency_review":"The text is internally consistent. It may be helpful to recheck the consistency in using X and x.","modularity_rating":4,"modularity_review":"I like the way examples are presented. It would be great to avoid long texts without gaps. For example, see Properties of the Student's t-Distribution in Page 419. I wish the text were written using LaTeX which produces better style and font. \r\n\r\nMy biggest problem with the modularity is that the authors did not provide nice boxes for major definitions and theorems which can be found in most other introductory textbooks. We can do better than just bold fonts.","organization_rating":5,"organization_review":"The chapters are organized well. Sections within some chapters could be reorganized. In chapter 2, quartiles and boxplots could be merged to a single section which should come after mean/median section.","interface_rating":5,"interface_review":"There are no major issues with the interface and navigation. The authors could check the balance of math equations being displayed inline and center-aligned. Some figures could be resized to make them look nicer.","grammatical_rating":5,"grammatical_review":"I did not find grammatical errors.","cultural_rating":5,"cultural_review":"The text is not culturally insensitive or offensive in any way.","overall_rating":9,"overall_review":"I also see the online version of the textbook at https://stats.libretexts.org/. I hope Openstax and libretexts are collaborating.\r\n\r\nAlso it is nice to see online homework for this textbook on MyOpenMath. There is only one template with chapter-wise homework. I wish there were more.","created_at":"2026-02-12T11:25:33.000-06:00","updated_at":"2026-02-12T11:25:33.000-06:00"}],"url":"https://open.umn.edu/opentextbooks/%20/textbooks/introductory-statistics-2013","updated_at":"2026-05-18T12:03:50.000-05:00"}],"links":{"self":"https://open.umn.edu/opentextbooks/%20/subjects/applied.json?page=1","total_pages":6,"total_count":51,"next":"https://open.umn.edu/opentextbooks/%20/subjects/applied.json?page=2"}}