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    Collaborative Statistics

    (18 reviews)

    Barbara Illowsky, De Anza College

    Susan Dean, De Anza College

    Copyright Year:

    ISBN 13: 9780978745073

    Publisher: OpenStax CNX

    Language: English

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    CC BY

    Reviews

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    Reviewed by Jennifer Koran, Associate Professor, Southern Illinois University Carbondale on 3/31/21

    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. read more

    Reviewed by Noureddine Benchama, Unlimited Math faculty, Minnesota State on 3/25/19

    I recommend enriching the book by a section on MISLEADING statistics. The 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. read more

    Reviewed by Sharon Emerson-Stonnell, Professor, Longwood University on 3/1/19

    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. ... read more

    Reviewed by Jenna Kowalski, Mathematics Instructor, Minnesota State on 2/6/19

    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... read more

    Reviewed by David Grollimund, Assistant Professor, Colorado State University - Pueblo on 2/1/18

    The 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... read more

    Reviewed by Whitney Zimmerman, Assistant Teaching Professor, The Pennsylvania State University on 2/1/18

    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... read more

    Reviewed by Angela Fishman, Assistant Teaching Professor, Penn State University on 2/1/18

    The contents are very typical of any introductory statistics book and more than enough for a 3-credit course for non-majors. read more

    Reviewed by Larry Musolino, Lecturer, Mathematics, Penn State University on 2/1/18

    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... read more

    Reviewed by Deborah Wall, Asst. Professor, American University on 2/1/18

    Book covers the topics we currently cover in our Basic Statistics course read more

    Reviewed by Deborah Hendricks, Clinical Associate Professor, West Virginia University on 12/5/16

    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,... read more

    Reviewed by Emily Rauscher, Assistant Professor, University of Kansas on 8/21/16

    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... read more

    Reviewed by Christopher Stapel, Community Faculty, Metropolitan State University on 8/21/16

    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... read more

    Reviewed by Kenneth Cheng, Instructor, Portland Community College on 1/7/16

    It covers essentially all the topics that would be expected in an introductory statistics course. read more

    Reviewed by Mamfe Osafo, Mathematics Instructor, Centrral Lakes College on 1/7/16

    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. read more

    Reviewed by Kurt Colvin, Professor, California Polytechnic State University on 7/15/14

    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... read more

    Reviewed by Shane Rollans, Senior Lecturer, Thompson Rivers University on 10/9/13

    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... read more

    Reviewed by RIchard Lockhart, Professor and Chair, Simon Fraser University on 10/9/13

    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... read more

    Reviewed by Robin Susanto, Instructor, Langara College on 10/9/13

    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... read more

    Table of Contents

    • 1 Sampling and Data
    • 2 Descriptive Statistics
    • 3 Probability Topics
    • 4 Discrete Random Variables
    • 5 Continuous Random Variables
    • 6 The Normal Distribution
    • 7 The Central Limit Theorem
    • 8 Confidence Intervals
    • 9 Hypothesis Testing: Single Mean and Single Proportion
    • 10 Hypothesis Testing: Two Means, Paired Data, Two Proportions
    • 11 The Chi-Square Distribution
    • 12 Linear Regression and Correlation
    • 13 F Distribution and ANOVA
    • 14 Appendix
    • 15 Tables

    Ancillary Material

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    About the Book

    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.

    About the Contributors

    Authors

    Barbara Illowsky is a Professor of Mathematics & Statistics at De Anza College in Cupertino, California. PhD in Education from Capella University.  

     

    Susan Dean is a mathematics professor at De Anza College in Cupertino, California.  

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