OpenIntro Statistics, Third Edition

OpenIntro Statistics, Third Edition

An open-source textbook for introductory statistics. It has been used in dozen courses including ones at Princeton University, and the University of Southern California.

Tag(s): Statistics

Publication date: 13 Jan 2016

ISBN-10: 194345003X

ISBN-13: 9781943450039

Paperback: 436 pages

Views: 3,520

Type: N/A

Publisher: OpenIntro, Inc.

License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

Post time: 30 Jun 2016 04:55:00

OpenIntro Statistics, Third Edition

OpenIntro Statistics, Third Edition An open-source textbook for introductory statistics. It has been used in dozen courses including ones at Princeton University, and the University of Southern California.
Tag(s): Statistics
Publication date: 13 Jan 2016
ISBN-10: 194345003X
ISBN-13: 9781943450039
Paperback: 436 pages
Views: 3,520
Document Type: N/A
Publisher: OpenIntro, Inc.
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Post time: 30 Jun 2016 04:55:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported:
You are free to:

Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material

The licensor cannot revoke these freedoms as long as you follow the license terms.

Click here to read the full license.
From the Preface:
Diez, Barr and Cetinkaya Rundel wrote:This book may be downloaded as a free PDF at openintro.org.

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.
(2) You don’t have to be a math guru to learn from real, interesting data.
(3) Data is messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world.

More information is available at the book webpage.




About The Author(s)


Christopher D. Barr was a Research Assistant Professor, in the Texas Institute for Measurement, Evaluation, and Statistics (TIMES), at the University of Houston. He now works as an Analyst at Varadero Capital. His research interests include application of multilevel and latent variable modelling techniques for studying nested data structures, particularly in the area of teacher and school level effects on students’ educational outcomes.

Christopher D. Barr

Christopher D. Barr was a Research Assistant Professor, in the Texas Institute for Measurement, Evaluation, and Statistics (TIMES), at the University of Houston. He now works as an Analyst at Varadero Capital. His research interests include application of multilevel and latent variable modelling techniques for studying nested data structures, particularly in the area of teacher and school level effects on students’ educational outcomes.


Mine Çetinkaya-Rundel is the Director of Undergraduate Studies and an Assistant Professor of the Practice in the Department of Statistical Science at Duke University. Her research focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education.

Mine Çetinkaya-Rundel

Mine Çetinkaya-Rundel is the Director of Undergraduate Studies and an Assistant Professor of the Practice in the Department of Statistical Science at Duke University. Her research focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education.


Dr. Diez is a Quantitative Analyst at Google/Youtube where he works with massive data sets and performs statistical analyses in areas such as user behavior and forecasting.

David Diez

Dr. Diez is a Quantitative Analyst at Google/Youtube where he works with massive data sets and performs statistical analyses in areas such as user behavior and forecasting.


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