Multiple Authors, Openstax College
Pub Date: 2013
ISBN 13: 978-1-9381682-0-8
Conditions of Use
This Introductory Statistics book covers all the introductory areas/concepts very thoroughly with the exception of Counting methods such as read more
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.
Per my review and use, I have found no errors.
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
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.
Text is consistent.
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.
The topics are presented in a typical, logical order for an introductory statistics course.
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.
Grammar is fine.
This book has many examples and assignments that cover many different and diverse topics without being offensive or heavy in one area.
Introductory Statistics is comprehensive and includes all the topics needed for an introductory course in statistics. In the preface, you are given read more
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.
I found no inconsistencies, errors or bias throughout the textbook’s content.
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.
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.
I found all the chapters to be consistent in both layout and breakdown.
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.
The topics are presented in an order consistent with any high priced introductory statistics textbook I have used.
I found the interface to be very consistent and there were no images distorted.
In the various chapters I reviewed. I found no grammar errors.
I found the textbook to be neutral with no insensitive or offensive materials. It appears very inclusive.
I found the textbook very useful and better than some high priced textbooks and plan on using it in upcoming semesters.
Introductory Statistics includes all the topics critical to a first course in college statistics designed for a wide range of majors and programs. It read more
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.
I have not found anything that is inaccurate, in error or biased.
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.
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.
The text is consistent in layout and approach to topics. Terminology is used in a consistent way throughout the chapters.
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.
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.
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.
I have not found any significant grammatical errors in the text book.
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.
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.
This text covers almost all of the concepts required in an introductory or sophomore level statistics course. However, there is one topic omission read more
This text covers almost all of the concepts required in an introductory or sophomore level statistics course. However, 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.
Beyond the authors' errata which is available separately on textbook's webpage, I have found the textbook to be error-free and accurate.
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.
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.
The text is consistent in its terminology and framework.
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.
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.
The text is free of any issues. There are no navigation problems nor any display issues.
There are no grammatical errors.
I found the text to be culturally respectful and inclusive with regard to gender, ethic background, etc.
This text is a good introduction to statistical methods. It presents formulas and techniques in a clear way with detailed examples. The 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.
The text covers all of the topics that are included in the Minnesota Transfer Curriculum for an introductory statistics course. Calculator read more
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. The 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. Type I and Type II errors are given good coverage with the introductory hypothesis testing. Table 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. Table F2 includes a chart showing the symbols used throughout a statistics course and gives its meaning and the associated topic for its use.
The content is generally accurate. There are some minor typos which might lead to confusion for students. A few noted below: Example 5.8 P(x < 5) = 1 – e(-0.25)(5) = 0.7135 should read P(x < 5) = 1 – e^(-0.25)(5) = 0.7135 In 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” Example 12.8 Figure 12-15 r = - 0.624-0.532, therefore r is significant, should read Figure 12-15 r = - 0.624 < - 0.532, therefore r is significant.
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. There 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. Necessary updates should be relatively easy to implement.
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.
There did not appear to be any issues with consistency in terminology or framework.
The organization of this book allows for smaller reading sections to be easily assigned. Realignment of subunits should not provide disruption to the reader.
The topics are arranged in an order that follows natural progression in a statistics course. They are addressed logically and given adequate coverage.
images/charts, and any other display features that may distract or confuse the reader. The 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. Listing the probability of A and B as P(AANDB) is not very readable. [3.1 Terminology]
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]
This text refers to many different cultures and ethnic backgrounds. The examples are respectful of differences in our society.
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. An 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. I would consider this text for adoption, but not without exploring other options that are available.
The text covers all of the major concepts students would be expected to learn in an introductory statistics course including sampling and data, read more
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.
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.
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.
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.
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.
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.
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.
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.
The text contains no grammatical errors and is well-written.
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, the text is highly comprehensive, covering a wide array of statistical concepts and including numerous examples and sample problems.
This book is sufficiently comprehensive for a non-majors introductory statistics course. In terms of content, it offers an adequate number of topics read more
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.
I did not find any obvious errors in the calculations or formulas.
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.
The material is presented clearly. Some of the sections are a little bit “wordy” but this does not take away from the overall clarity.
In the sections I reviewed, the notation and terminology was consistent.
The organization and chunking of material in each section is appropriate for an introductory statistics student.
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.
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.
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.
The text did not seem to be particularly culturally relevant. I did not find any evidence of it being culturally offensive.
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 read more
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.
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.
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.
The textbook is very clear and concise, for the most part.
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.
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.
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.
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.
Of the errors I've found in this text, none of them were grammatical errors.
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, I'm very happy with this textbook.
This textbook covers all of the standard topics usually covered in ? descriptive and inferential statistics textbooks for non- mathematicians. The read more
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. The 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. The 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.
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.
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
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.
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.
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.
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.
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.
I’ve not found any grammatical errors in this textbook (but English is not my native language). It is well written.
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.
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. The textbook available to students for free and with addition of the computational computer technologies can be recommended for a community college basic statistics courses.
A Statistics textbook mostly have a standard structure. This bookk covers major subjects of the course. Central limit theorem is given a whole read more
A Statistics textbook mostly have a standard structure. This bookk covers major subjects of the course. Central limit theorem is given a whole chapter, which is good because of its importance. However, I would like to see these more. No 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. Normality test would be needed. No Goodness-of-fit test or probability plot is explained. Normality test is important for the inference statistics. It would be good to explain mean and variance of linear combination of variables, such as E[5X+2Y]= 5E[X]+2E[Y]. It will be better to give a form of PDF (or PMF) of discrete random variables. Confidence Interval formula of F-distrbution would be better.
This book is accurate.
Elementary Statitics theory is not changed quickly. Although the application examples can be more or less current, this book is uptodated.
This book is clear in its contents. This book is actually carefully written for better understandinig of the materials.
Yes. No problem.
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.
Yes. Again, the standard structure of Statistics textbooks. Explanantions are simple and clear.
No interface problems.
(1) The competition of Statistics textbooks in the market is very high, and there are many good books available (at high prices). One 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.” (2) It 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. (3) This 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). The lecture video, which is helpful, is partially based on hand writing. I would prefer the video to be completely based on PPT. No PowerPoint lecture note is provided. This will make the preparation of lecture note time taking. (4) The 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. (5) Editing The numbers in tables can be centered for a better appearance. The “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. Solution of homework of each chapter is given in the chapter, which is nice.
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 read more
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.
I could not find any typos. I feel the text was accurate, error-free, and unbiased.
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.
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
The text is consistent in terms of terminology and framework.
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.
The organization of the text is very similar to other introductory statistics texts. The topics are presented in a logical, clear fashion.
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.
I did not notice any grammatical errors.
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.
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.
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 read more
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.
I did not notice any glaring errors. There are some awkward word choices, which I discuss under "grammar".
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.
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. I 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.
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.
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.
The book is organized in the same way as other statistics textbooks.
Interface issues are minimal. Occasionally, there are large spaces between items (for example, page 72). This can be a little distracting.
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.
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).
This textbook covers all of the standard topics usually covered in an undergradate introductory text including hyhothresis testing and ANOVA. The read more
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.
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.
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.
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.
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.
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.
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.
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.
I did not spot and such errors. I specifically read through ALL of the end of chapter glossaries.
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.
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.
This book covers all the topics typically covered in an introductory level statistics course from an introduction to probability and the basics f read more
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.
The work is free of errors. Sample problems are drawn from a wide variety of subjects and topics.
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.
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.
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
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.
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..
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
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.
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.
This book covers all necessary content areas for an introduction to Statistics course for non-math majors. The text book provides an effective index, read more
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.
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.
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.
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.
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.
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.
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.
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.
I did not find any grammatical errors.
I did not see any culturally insensitive material or exercises in the text.
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.
Table of Contents
- Sampling and Data
- Descriptive Statistics
- Probability Topics
- Discrete Random Variables
- Continuous Random Variables
- The Normal Distribution
- The Central Limit Theorem
- Confidence Intervals
- Hypothesis Testing with One Sample
- Hypothesis Testing with Two Samples
- The Chi-Square Distribution
- Linear Regression and Correlation
- F Distribution and One-Way ANOVA
About the Book
Introductory Statistics follows the scope and sequence of a one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean, which has been widely adopted. Introductory Statistics includes innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful and memorable, so that students can draw a working knowledge from it that will enrich their future studies and help them make sense of the world around them. The text also includes Collaborative Exercises, integration with TI-83,83+,84+ Calculators, technology integration problems, and statistics labs.
OpenStax College has compiled many resources for faculty and students, from faculty-only content to interactive homework and study guides.
About the Contributors
Senior Contributing Authors
Barbara Illowsky, De Anza College
Susan Dean, De Anza College