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Statistics for People Who (Think They) Hate Statistics Using R
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Statistics for People Who (Think They) Hate Statistics Using R

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August 2019 | 536 pages | SAGE Publications, Inc

Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS® and Excel® versions are joined by a text for use with the R software, Statistics for People Who (Think They) Hate Statistics Using R. New co-author Leslie A. Shaw carries forward Salkind’s signature humorous, personable, and informative approach as the text guides students in a grounding of statistical basics and R computing, and the application of statistics to research studies. The book covers various basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more.  

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Preface
 
Acknowledgments
 
About the Authors
 
Digital Resources
 
PART I • YIPPEE! I’M IN STATISTICS
 
Chapter 1 • Statistics or Sadistics? It’s Up to You
What You Will Learn in This Chapter

 
Why Statistics?

 
A 5-Minute History of Statistics

 
Statistics: What It Is (and Isn’t)

 
What Am I Doing in a Statistics Class?

 
Ten Ways to Use This Book (and Learn Statistics at the Same Time!)

 
What Else Does This Book Contain?

 
Summary

 
Time to Practice

 
Student Study Site

 
 
PART II • WELCOME TO THE INTERESTING, USEFUL, FLEXIBLE, FUN, AND (VERY) DEEP WORLDS OF R AND RSTUDIO
 
Chapter 2 • Here’s Why We Love R and How to Get Started
What You Will Learn in This Chapter

 
A Very Short History of R

 
The Pluses of Using R

 
The Minuses of Using R

 
Other Reasons to Use R?

 
A Short Note to You (and to Your Instructor) About Open Source (Again!)

 
Where to Find and Download R

 
Packages and Functions in R

 
A Note About Formatting

 
Bunches of Data—Free!

 
Getting R Help

 
Getting Help on Help

 
Some Important Lingo

 
Where to Find RStudio and How to Install It

 
Take RStudio for a Test Ride

 
Ordering From RStudio

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 3 • Using RStudio: Much Easier Than You Think
What You Will Learn in This Chapter

 
The Grand Tour and All About Those Four Panes

 
RStudio Pane Goodies

 
Showing Your Stuff—Working With Menus and Tabs and a Sample Data Analysis Using RStudio

 
The Basics: +, –, ?, *, and More: Using Operators

 
Working With Data

 
Let’s See What’s in the Workspace

 
Reading in Established Data Sets

 
Oops! How Do You Correct Console Errors?

 
Pointing and Clicking to Open a Data Set

 
Computing Some Statistics

 
Ten Important Things to Remember About R and RStudio (but Not Necessarily in Order of Importance)

 
Summary

 
Time to Practice

 
Student Study Site

 
 
PART III • SIGMA FREUD AND DESCRIPTIVE STATISTICS
 
Chapter 4 • Computing and Understanding Averages: Means to an End
What You Will Learn in This Chapter

 
Computing the Mean

 
Computing the Median

 
Computing the Mode

 
When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)

 
Using the Computer to Compute Descriptive Statistics

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 5 • Understanding Variability: Vive la Différence
What You Will Learn in This Chapter

 
Why Understanding Variability Is Important

 
Computing the Range

 
Computing the Standard Deviation

 
Step-by-Step

 
What’s the Big Deal?

 
Computing the Variance

 
Using R to Compute Measures of Variability

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 6 • Creating Graphs: A Picture Really Is Worth a Thousand Words
What You Will Learn in This Chapter

 
Why Illustrate Data?

 
Ten Ways to a Great Graphic

 
First Things First: Creating a Frequency Distribution

 
The Plot Thickens: Creating a Histogram

 
The Next Step: A Frequency Polygon

 
Cumulating Frequencies

 
Other Cool Ways to Chart Data

 
Using the Computer (R, That Is) to Illustrate Data

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 7 • Computing Correlation Coefficients: Ice Cream and Crime
What You Will Learn in This Chapter

 
What Are Correlations All About?

 
Computing a Simple Correlation Coefficient

 
Understanding What the Correlation Coefficient Means

 
A Determined Effort: Squaring the Correlation Coefficient

 
Computing the Correlation Coefficient by Entering Data

 
Computing the Correlation Coefficient by Importing a File

 
Other Cool Correlations

 
Parting Ways: A Bit About Partial Correlation

 
Using R to Compute Partial Correlations

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 8 • An Introduction to Understanding Reliability and Validity: Just the Truth
What You Will Learn in This Chapter

 
An Introduction to Reliability and Validity

 
Reliability: Doing It Again Until You Get It Right

 
Different Types of Reliability

 
Computing Cronbach’s Alpha

 
Using R to Calculate Cronbach’s Alpha

 
Understanding the R Output

 
Computing Interrater Reliability

 
How Big Is Big? Finally: Interpreting Reliability Coefficients

 
Validity: Whoa! What Is the Truth?

 
A Last Friendly Word

 
Validity and Reliability: Really Close Cousins

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
PART IV • TAKING CHANCES FOR FUN AND PROFIT
 
Chapter 9 • Hypotheticals and You: Testing Your Questions
What You Will Learn in This Chapter

 
So You Want to Be a Scientist

 
Samples and Populations

 
The Null Hypothesis

 
The Research Hypothesis

 
What Makes a Good Hypothesis?

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 10 • Probability and Why It Counts: Fun With a Bell-Shaped Curve
What You Will Learn in This Chapter

 
Why Probability?

 
The Normal Curve (a.k.a. the Bell-Shaped Curve)

 
Our Favorite Standard Score: The z Score

 
Hypothesis Testing and z Scores: The First Step

 
Fat and Skinny Frequency Distributions

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
PART V • SIGNIFICANTLY DIFFERENT: USING INFERENTIAL STATISTICS
 
Chapter 11 • Significantly Significant: What It Means for You and Me
What You Will Learn in This Chapter

 
The Concept of Significance

 
Significance Versus Meaningfulness

 
An Introduction to Inferential Statistics

 
An Introduction to Tests of Significance

 
Be Even More Confident

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 12 • The One-Sample z Test: Only the Lonely
What You Will Learn in This Chapter

 
Introduction to the One-Sample z Test

 
The Path to Wisdom and Knowledge

 
Computing the z Test Statistic

 
Using R to Perform a z Test

 
Special Effects: Are Those Differences for Real?

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 13 • t(ea) for Two: Tests Between the Means of Different Groups
What You Will Learn in This Chapter

 
Introduction to the t Test for Independent Samples

 
The Path to Wisdom and Knowledge

 
Computing the t Test Statistic

 
The Effect Size and t(ea) for Two

 
Using R to Perform a t Test

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 14 • t(ea) for Two (Again): Tests Between the Means of Related Groups
What You Will Learn in This Chapter

 
Introduction to the t Test for Dependent Samples

 
The Path to Wisdom and Knowledge

 
Computing the t Test Statistic

 
Using R to Perform a t Test

 
The Effect Size for t(ea) for Two (Again)

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 15 • Two Groups Too Many? Try Analysis of Variance
What You Will Learn in This Chapter

 
Introduction to Analysis of Variance

 
The Path to Wisdom and Knowledge

 
Different Flavors of ANOVA

 
Computing the F Test Statistic

 
Using R to Compute the F Ratio

 
The Effect Size for One-Way ANOVA

 
But Where Is the Difference?

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 16 • Two Too Many Factors: Factorial Analysis of Variance—A Brief Introduction
What You Will Learn in This Chapter

 
Introduction to Factorial Analysis of Variance

 
The Path to Wisdom and Knowledge

 
A New Flavor of ANOVA

 
All of Those Effects

 
The Main Event: Main Effects in Factorial ANOVA

 
The Other Rows

 
Plotting the Means by Group

 
Even More Interesting Interaction Effects

 
Assumptions About Variances

 
Using R to Compute the F Ratio

 
Computing the Effect Size for Factorial ANOVA

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 17 • Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?
What You Will Learn in This Chapter

 
Introduction to Testing the Correlation Coefficient

 
The Path to Wisdom and Knowledge

 
Computing the Test Statistic

 
Causes and Associations (Again!)

 
Using R to Compute a Correlation Coefficient (Again)

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 18 • Using Linear Regression: Predicting the Future
What You Will Learn in This Chapter

 
Introduction to Linear Regression

 
What Is Prediction All About?

 
The Logic of Prediction

 
Drawing the World’s Best Line (for Your Data)

 
How Good Is Your Prediction?

 
Using R to Compute the Regression Line

 
Understanding the R Output

 
The More Predictors the Better? Maybe

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
PART VI • MORE STATISTICS! MORE TOOLS! MORE FUN!
 
Chapter 19 • Chi-Square and Some Other Nonparametric Tests: What to Do When You’re Not Normal
What You Will Learn in This Chapter

 
Introduction to Nonparametric Statistics

 
Introduction to the Goodness-of-Fit (One-Sample) Chi-Square

 
Computing the Goodness-of-Fit Chi-Square Test Statistic

 
Introduction to the Test of Independence Chi-Square

 
Computing the Test of Independence Chi-Square Test Statistic

 
Using R to Perform Chi-Square Tests

 
Understanding the R Output

 
Other Nonparametric Tests You Should Know About

 
Real-World Stats

 
Summary

 
Time to Practice

 
Student Study Site

 
 
Chapter 20 • Some Other (Important) Statistical Procedures You Should Know About
What You Will Learn in This Chapter

 
Multivariate Analysis of Variance

 
Repeated-Measures Analysis of Variance

 
Analysis of Covariance

 
Multiple Regression

 
Multilevel Models

 
Meta-Analysis

 
Logistic Regression

 
Factor Analysis

 
Path Analysis

 
Structural Equation Modeling

 
Summary

 
Student Study Site

 
 
Appendix A: More Fun Stuff With R and RStudio
 
Appendix B: Tables
 
Appendix C: Data Sets
 
Appendix D: Answers to Practice Questions
 
Appendix E: Math: Just the Basics
 
Appendix F: The 10 (or More) Best (and Most Fun) Internet Sites for Statistics Stuff
 
Appendix G: The 10 Commandments of Data Collection
 
Appendix H: Glossary
 
Appendix I: The Reward
 
Index

Supplements

Instructor Resource Site
edge.sagepub.com/salkindshaw

SAGE edge for instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students with:
  • a password-protected site for complete and protected access to all text-specific instructor resources;  
  • R syntax and data files are available for download and use with exercises in the book;
  • test banks that provide a diverse range of ready-to-use options that save you time. You can also easily edit any question and/or insert your own personalized questions;
  • multimedia content featuring original screencast tutorial videos that demonstrate setting up the data and running selected problems in R meet the learning needs of today’s media-savvy students and bring concepts to life; and
  • editable, chapter-specific PowerPoint® slides that offer complete flexibility for creating a multimedia presentation for your course.
 
Student Study Site
SAGE edge for students enhances learning, it’s easy to use, and offers:
  • an open-access site that makes it easy for students to maximize their study time, anywhere, anytime;
  • R syntax and data files are available for download and use with exercises in the book;
  • video resources that bring concepts to life, are tied to learning objectives, and are curated and produced exclusively for this text, featuring: 
    • Screencast tutorial videos demonstrate setting up the data and running selected problems in R
  • eFlashcards that strengthen understanding of key terms and concepts; and
  • eQuizzes that allow students to practice and assess how much they’ve learned and where they need to focus their attention.
 

“Salkind is the master of presenting options for data analysis in a logical, straightforward manner so students are able to focus on the meaning rather than the math of statistics.”

Jacqueline Craven
Delta State University

“The (late) Dr. Salkind's text continues (with Dr. Shaw's R-integration) to be a readable statistical text that provides a gentle yet surprisingly comprehensive introduction to statistics. For anyone teaching a basic level, introductory level, or first class in statistics, I cannot think of a better text. This R update adds an important element to the Excel and SPSS versions of this inimitable text.”

Jeff Savage
Cornerstone University

“There are many textbooks on R, textbooks on Statistics, and textbooks on R and Statistics that are extremely technical, and difficult to read and use. This textbook is the golden mean!”

Shlomo Sawilowsky
Wayne State University

“The text makes statistics accessible for even the most ‘math-phobic’ student and ‘demystifies’ the world of R. It is the most comprehensive statistics textbook that walks students through both the mathematical and software steps of doing statistics.”

Daniel Scheller
University of Texas at El Paso

“The value of this text is that it presents complex ideas in a way that people can relate to—using examples, walking through steps, and providing all the additional tools needed to succeed in an introduction to statistics course.”

Candace Forbes Bright
East Tennessee State University

“This text is a thorough and effective packaging of statistical analysis and computational techniques in the R language, which would be highly useful to students from a variety of backgrounds.”

Matthew Phillips
University of North Carolina, Charlotte

“Salkind and Shaw do an excellent job of presenting difficult statistical concepts and tools in a highly accessible manner. One of the best introductory statistics textbooks available.”

Scott Comparato
Southern Illinois University

“Salkind's book has always been the very best text for introducing my undergraduate students to statistics. Now, it introduces R as well. I will recommend this book to everyone.”

Matthew R. Miles
Brigham Young University, Idaho

“As with previous editions of this book by Dr. Salkind, this textbook captures the essence of Dr. Salkind's style, talent, and expertise in explaining statistics. Including information and instruction on R software for analysis is a benefit since students can now access a free software program.”

Mary Beth Zeni
Ursuline College

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