Read more about Introductory Statistics with Randomization and Simulation - First Edition

Introductory Statistics with Randomization and Simulation - First Edition

(5 reviews)

David Diez, Google/YouTube

Christopher Barr, Varadero Capital

Mine Çetinkaya-Rundel, Duke University

Copyright Year: 2014

Publisher: OpenIntro

Language: English

Formats Available

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Learn more about reviews.

Reviewed by David Fainstein, Assistant Professor, Seattle University on 6/1/23

The chapters are comprehensive enough to provide a solid introduction. Supplementary materials add to the robustness of explanation and conceptual grounding. read more

Reviewed by Jeremy Wojdak, Professor, Radford University on 1/26/20

The book covers content typical of an introductory statistics course, plus a nice chapter on simulation. Given there are only six chapters, it means a lot of content ends up in each chapter, for better or worse. Exercises are numerous, diverse,... read more

Reviewed by Onyumbe Enumbe Lukongo, Associate Professor of Public Policy, Southern University on 4/25/19

The exposition of materials allows readers to grasp concepts and apply successful knowledge gained to real world examples. read more

Reviewed by Christine Spinka, Assistant Teaching Professor, MOBIUS on 1/15/19

This text provides thorough coverage of a wide variety of introductory statistical concepts. While no text at this level contains all possible topics, this book provides excellent coverage of important concepts for using statistics to examine... read more

Reviewed by Kouame N'Guetta, Adjunct Lecturer, LaGuardia Community College on 5/21/18

The text covers all areas and ideas of the subject appropriately, read more

Table of Contents

1. Introduction to data.

2. Foundations for inference.

3. Inference for categorical data.

4. Inference for numerical data.

5. Introduction to linear regression.

6. Multiple and logistic regression.

Appendix A. Probability.

Ancillary Material

  • OpenIntro
  • About the Book

    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 interesting, real data.

    (3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

    Textbook overview

    The chapters of this book are as follows:1. Introduction to data. Data structures, variables, summaries, graphics, and basic data collection techniques.2. Foundations for inference. Case studies are used to introduce the ideas of statistical inference with randomization and simulations. The content leads into the standard parametric framework, with techniques reinforced in the subsequent chapters.1It is also possible to begin with this chapter and introduce tools from Chapter 1 as theyare needed.3. Inference for categorical data. Inference for proportions using the normal and chi-square distributions, as well as simulation and randomization techniques.4. Inference for numerical data. Inference for one or two sample means using the t distribution, and also comparisons of many means using ANOVA. A special section for bootstrapping is provided at the end of the chapter.5. Introduction to linear regression. An introduction to regression with two variables. Most of this chapter could be covered immediately after Chapter 1.6. Multiple and logistic regression. An introduction to multiple regression and logistic regression for an accelerated course.

    Appendix A. Probability. An introduction to probability is provided as an optional reference. Exercises and additional probability content may be found in Chapter 2 of OpenIntro Statistics at Instructor feedback suggests that probability, if discussed, is best introduced at the very start or very end of the course.

    About the Contributors


    David Diez is a Senior Quantitative Analyst at Google/YouTube.

    Christopher Barr is an Investment Analyst at Varadero Capital.

    Dr. Mine Çetinkaya-Rundel is the Director of Undergraduate Studies and an Associate Professor of the Practice in the Department of Statistical Science at Duke University. She received her Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University’s Stern School of Business. Her work focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education.

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