Neil J. Salkind & Bruce B. Frey 
Statistics for People Who (Think They) Hate Statistics [EPUB ebook] 

A Note to the Student: Why We Wrote This Book
Acknowledgments
And Now, About the Seventh Edition . . .
About the Authors
PART I • YIPPEE! I’M IN STATISTICS
Chapter 1 • Statistics or Sadistics? It’s Up to You
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!)
About the Book’s Features
Key to Difficulty Icons
Glossary
Summary
Time to Practice
PART II • SIGMA FREUD AND DESCRIPTIVE STATISTICS
Chapter 2 • Computing and Understanding Averages: Means to an End
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 SPSS to Compute Descriptive Statistics
Summary
Time to Practice
Chapter 3 • Understanding Variability: Vive la Différence
Why Understanding Variability Is Important
Computing the Range
Computing the Standard Deviation
Computing the Variance
Using SPSS to Compute Measures of Variability
Summary
Time to Practice
Chapter 4 • Creating Graphs: A Picture Really Is Worth a Thousand Words
Why Illustrate Data?
Ten Ways to a Great Figure (Eat Less and Exercise More?)
First Things First: Creating a Frequency Distribution
The Plot Thickens: Creating a Histogram
The Next Step: A Frequency Polygon
Other Cool Ways to Chart Data
Using the Computer (SPSS, That Is) to Illustrate Data
Summary
Time to Practice
Chapter 5 • Computing Correlation Coefficients: Ice Cream and Crime
What Are Correlations All About?
Computing a Simple Correlation Coefficient
Squaring the Correlation Coefficient: A Determined Effort
Other Cool Correlations
Parting Ways: A Bit About Partial Correlation
Summary
Time to Practice
Chapter 6 • An Introduction to Understanding Reliability and Validity: Just the Truth
An Introduction to Reliability and Validity
Reliability: Doing It Again Until You Get It Right
Different Types of 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
Summary
Time to Practice
PART III • TAKING CHANCES FOR FUN AND PROFIT
Chapter 7 • Hypotheticals and You: Testing Your Questions
So You Want to Be a Scientist
Samples and Populations
The Null Hypothesis
The Research Hypothesis
What Makes a Good Hypothesis?
Summary
Time to Practice
Chapter 8 • Probability and Why It Counts: Fun With a Bell-Shaped Curve
Why Probability?
The Normal Curve (aka the Bell-Shaped Curve)
Our Favorite Standard Score: The z Score
Fat and Skinny Frequency Distributions
Summary
Time to Practice
PART IV • SIGNIFICANTLY DIFFERENT: USING INFERENTIAL STATISTICS
Chapter 9 • Significantly Significant: What It Means for You and Me
The Concept of Significance
Significance Versus Meaningfulness
An Introduction to Inferential Statistics
An Introduction to Tests of Significance
Be Even More Confident
Summary
Time to Practice
Chapter 10 • The One-Sample z Test: Only the Lonely
Introduction to the One-Sample z Test
The Path to Wisdom and Knowledge
Computing the z Test Statistic
Using SPSS to Perform a z Test
Special Effects: Are Those Differences for Real?
Summary
Time to Practice
Chapter 11 • t(ea) for Two: Tests Between the Means of Different Groups
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 SPSS to Perform a t Test
Summary
Time to Practice
Chapter 12 • t(ea) for Two (Again): Tests Between the Means of Related Groups
Introduction to the t Test for Dependent Samples
The Path to Wisdom and Knowledge
Computing the t Test Statistic
Using SPSS to Perform a Dependent t Test
The Effect Size for t(ea) for Two (Again)
Summary
Time to Practice
Chapter 13 • Two Groups Too Many? Try Analysis of Variance
Introduction to Analysis of Variance
The Path to Wisdom and Knowledge
Different Flavors of Analysis of Variance
Computing the F Test Statistic
Using SPSS to Compute the F Ratio
The Effect Size for One-Way ANOVA
Summary
Time to Practice
Chapter 14 • Two Too Many Factors: Factorial Analysis of Variance—A Brief Introduction
Introduction to Factorial Analysis of Variance
The Path to Wisdom and Knowledge
A New Flavor of ANOVA
The Main Event: Main Effects in Factorial ANOVA
Even More Interesting: Interaction Effects
Using SPSS to Compute the F Ratio
Computing the Effect Size for Factorial ANOVA
Summary
Time to Practice
Chapter 15 • Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?
Introduction to Testing the Correlation Coefficient
The Path to Wisdom and Knowledge
Computing the Test Statistic
Using SPSS to Compute a Correlation Coefficient (Again)
Summary
Time to Practice
Chapter 16 • Using Linear Regression: Predicting the Future
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 SPSS to Compute the Regression Line
The More Predictors the Better? Maybe
Summary
Time to Practice
PART V • MORE STATISTICS! MORE TOOLS! MORE FUN!
Chapter 17 • Chi-Square and Some Other Nonparametric Tests: What to Do When You’re Not Normal
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 SPSS to Perform Chi-Square Tests
Other Nonparametric Tests You Should Know About
Summary
Time to Practice
Chapter 18 • Some Other (Important) Statistical Procedures You Should Know About
Multivariate Analysis of Variance
Repeated-Measures Analysis of Variance
Analysis of Covariance
Multiple Regression
Meta-Analysis
Discriminant Analysis
Factor Analysis
Path Analysis
Structural Equation Modeling
Summary
Chapter 19 • Data Mining: An Introduction to Getting the Most Out of Your BIG Data
Our Sample Data Set—Who Doesn’t Love Babies?
Counting Outcomes
Pivot Tables and Cross-Tabulation: Finding Hidden Patterns
Summary
Time to Practice
Appendix A: SPSS Statistics in Less Than 30 Minutes
Appendix B: Tables
Appendix C: Data Sets
Appendix D: Answers to Practice Questions
Appendix E: Math: Just the Basics
Appendix F: A Statistical Software Sampler
Appendix G: The 10 (or More) Best (and Most Fun) Internet Sites for Statistics Stuff
Appendix H: The 10 Commandments of Data Collection
Appendix I: The Reward: The Brownie Recipe
Glossary
Index

Bruce B. Frey, Ph D,  is an award-winning researcher, author, teacher, and professor of educational psychology at the University of Kansas. He is the editor of The SAGE Encyclopedia of Educational Research, Measurement and Evaluation and the SAGE Encyclopedia of Educational Design. In addition to being the lead author for The Statistics for People Who (Think They) Hate Statistics series, his books for SAGE include There’s a Stat for That!, Modern Classroom Assessment, and 100 Questions (and Answers) About Tests and Measurement. He also wrote Statistics Hacks for O’Reilly Media. In his spare time, Bruce leads a secret life as Professor Bubblegum, host of a You Tube channel and Echo Valley, a podcast that celebrates bubblegum pop music of the late 1960s. The show is wildly popular with the young people.