Introductory Statistics

(7 reviews)


Douglas Shafer, University of North Carolina
Zhiyi Zhang, University of North Carolina

Pub Date:

ISBN 13: 978-1-4533448-7-3

Publisher: Saylor Foundation

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Reviewed by Sarah Clifton, Instructor, Southeastern Louisiana University, on 6/21/2017.

This text covers all the necessary points in an introductory Statistics glass with a well organized, user friendly index. Each chapter has a nice … read more



Reviewed by Russell Campbell, Associate Professor, University of Northern Iowa, on 12/6/2016.

I did not see any index or glossary. It covers the basic descriptive statistics, probability, and inferential statistics of an introductory course. … read more



Reviewed by Amit Verma , Adjunct Instructor , University of North Carolina at Greensboro , on 12/6/2016.

When comparing numerous statistical textbooks to this book, the level of comprehensiveness is consistent with other material published and in some … read more



Reviewed by Mamfe Osafo, Mathematics Instructor, Centrral Lakes College , on 1/8/2016.

The text covers some of the areas needed for an Introduction to Statistics or Elementary Statistics. For example, experimental design was not well … read more



Reviewed by Dr. Erik C. Korolenko, Professor, University Canada West, on 10/10/2013.

The text covers some of the areas of the subject, albeit not in-depth. Whether this approach is appropriate for an introductory course, depends … read more



Reviewed by Shivanand Balram, Senior Lecturer, Spatial Information Science, Simon Fraser University, on 10/10/2013.

Most introductory statistics texts use the logical structure of descriptive statistics, probability, and inferential statistics to deliver the … read more



Reviewed by Leslie Burkholder, Senior lecturer, University of British Columbia, on 10/10/2013.

The consensus introductory statistics curriculum is typically presented in three major units: (1) Descriptive statistics and study design … read more


Table of Contents

  • Chapter 1: Introduction
  • Chapter 2: Descriptive Statistics
  • Chapter 3: Basic Concepts of Probability
  • Chapter 4: Discrete Random Variables
  • Chapter 5: Continuous Random Variables
  • Chapter 6: Sampling Distributions
  • Chapter 7: Estimation
  • Chapter 8: Testing Hypotheses
  • Chapter 9: Two-Sample Problems
  • Chapter 10: Correlation and Regression
  • Chapter 11: Chi-Square Tests and F-Tests

About the Book

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.

About the Contributors


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.

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.