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This Fifth Edition of Neil J. Salkind’s Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel, presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Opening with an introduction to Excel, including coverage of how to use functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. New to the Fifth Edition is new co-author Bruce Frey who has added a new feature on statisticians throughout history (with a focus on the contributions of women and people of color). He has updated the "Real-World Stats” feature, and added more on effect sizes, updated the discussions on hypotheses, measurement concepts like validity and reliability, and has more closely tied analytical choices to the level of measurement of variables.

A website to accompany the book with resources for instructors and students is available at:

Chapter 1: Statistics or Sadistics? It’s Up to You
Chapter 2: Getting Started in Excel
Chapter 3: Computing and Understanding Averages: Means to an End
Chapter 4: Understanding Variability: Vive la Différence
Chapter 5: Creating Graphs: A Picture Really Is Worth a Thousand Words
Chapter 6: Computing Correlation Coefficients: Ice Cream and Crime
Chapter 7: Understanding Reliability and Validity: Just the Truth
Chapter 8: Hypotheticals and You: Testing Your Questions
Chapter 9: Probability and Why It Counts: Fun With a Bell-Shaped Curve
Chapter 10: Significantly Significant: What It Means for You and Me
Chapter 11: The One-Sample Z-Test: Only the Lonely
Chapter 12: t(ea) for Two: Tests Between the Means of Different Groups
Chapter 13: t(ea) for Two (Again): Tests Between the Means of Related Groups
Chapter 14: Analysis of Variance: Two Groups Too Many?
Chapter 15: Factorial Analysis of Variance: Two Too Many Factors
Chapter 16: Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?
Chapter 17: Using Linear Regression: Predicting the Future
Chapter 18: Chi-Square and Some Other Nonparametric Tests: What to Do When You’re Not Normal
Chapter 19: Some Other (Important) Statistical Procedures You Should Know About
Chapter 20: Data Mining: A Introduction to Getting the Most Out of Your BIG Data


Student Study Site

SAGE edge for Students  provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts
  • Data files allow you to follow along with the exercises in the book

Instructor Teaching Site
SAGE edge for Instructors supports teaching by making it easy to integrate quality content and create a rich learning environment for students.
  • Test banks provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert personalized questions to effectively assess students’ progress and understanding
  • Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for the course
  • Data files allow students to follow along with the exercises in the book

This is an updated version of the textbook we are currently using in the course.

Dr Rizwana Biviji
School for the Science of Health Care Delivery, Arizona State Univ-downtown
September 20, 2021

Helped adults to understand the concepts without jargon

Dr Gwendolyn c Dooley
Dean Of Education, Jackson State University
July 27, 2021
Key features
  • Coverage of the latest information on Excel 2019 appears throughout the book to help students get the most from the latest release of the software.
  • New co-author, Bruce Frey, brings his extensive teaching and textbook authoring experience to the new edition.
  • New feature “People Who Loved Statistics” profiles statisticians throughout history (with a focus on the contributions of women and people of color).
  • New coverage of effect sizes, updated discussions on hypotheses, measurement concepts like validity and reliability, and now more closely ties analytical choices to the level of measurement of variables.
  • Practical, easy-to-understand coverage of most important topics needed to succeed in the course, future jobs, and everyday life is presented in a warm, down-to-earth manner infused with humor and respect for the students.
  • Complete coverage of the Excel Data Analysis tools shows readers how they can be used for descriptive statistics, graphical representation of data, correlation, regression, and more.
  • Discussions of important topics, such as the normal curve, inference, and the central limit theorem—and their importance—help students master key concepts and skills.
  • Instructions on using Excel formula to compute reliability estimates, Chi-square values, and other non-parametric procedures prepare students to use the software when analyzing their own work.
  • A chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world.
  • Answers to exercises at the back of the book (with page references) make it easy for students to check their analyses and then quickly refer to the specific information they need to review.
  • Appendix E presents basic math instruction and practice exercises for those who need to brush up on their math skills.

For instructors

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