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# Statistics for People Who (Think They) Hate Statistics - International Student Edition

Seventh Edition

- Neil J. Salkind
- Bruce B. Frey - University of Kansas, USA

September 2019 | SAGE Publications, Inc

The bestselling **Statistics for People Who (Think They) Hate Statistics** is now in its **Seventh Edition** with new co-author Bruce B. Frey. This text teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. The authors take students through various statistical procedures, beginning with correlation and graphical representation of data and ending with inferential techniques and analysis of variance. In addition, the text provides instruction in SPSS, and includes reviews of more advanced techniques, such as reliability, validity, introductory non-parametric statistics, and more.

The new seventh edition includes:

- Retaining the student-friendly tone and presentation that made this text an international bestseller, new co-author Bruce Frey has added new examples, and reworked or expanded the explanations of many concepts to provide extra clarity.
- A key feature called "The Path to Wisdom and Knowledge": a flowchart in each of the main chapters showing readers how to select the appropriate test statistic.
- More on multiple regression, power and effect size, and a new feature on statisticians throughout history called "People (Who Liked) Statistics".

A Note to the Student: Why We Wrote This Book

Acknowledgements

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

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!)

About the Book’s Features

Key to Difficulty Icons

Glossary

Summary

Part II: Zigma Freud and Descriptive Statistics

Chapter 2. 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 SPSS to Compute Descriptive Statistics

Real-World Stats

Summary

Time to Practice

Chapter 3. Understanding Variability: Vivé la Différence

What You Will Learn in This Chapter

Why Understanding Variability Is Important

Computing the Range

Computing the Standard Deviation

Computing the Variance

Using SPSS to Compute Measures of Variability

Real-World Stats

Summary

Time to Practice

Chapter 4. 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 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

Real-World Stats

Summary

Time to Practice

Chapter 5. 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

Squaring the Correlation Coefficient: A Determined Effort

Other Cool Correlations

Parting Ways: A Bit About Partial Correlation

Real-World Stats

Summary

Time to Practice

Chapter 6. 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

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

Part III: Taking Chances for Fun and Profit

Chapter 7. 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

Chapter 8. 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

Fat and Skinny Frequency Distributions

Real-World Stats

Summary

Time to Practice

Part IV Significantly Different: Using Inferential Statistics

Chapter 9. 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

Chapter 10. 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 SPSS to Perform a Z Test

Special Effects: Are Those Differences for Real?

Real-World Stats

Summary

Time to Practice

Chapter 11. 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 SPSS to Perform a t Test

Real-World Stats

Summary

Time to Practice

Chapter 12. 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 SPSS to Perform a Dependent t Test

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

Real-World Stats

Summary

Time to Practice

Chapter 13. 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 Analysis of Variance

Computing the F Test Statistic

Using SPSS to Compute the F Ratio

The Effect Size for One-Way ANOVA

Real World Stats

Summary

Time to Practice

Chapter 14. 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

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

Real World Stats

Summary

Time to Practice

Chapter 15. 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

Using SPSS to Compute a Correlation Coefficient (Again)

Real World Stats

Summary

Time to Practice

Chapter 16. 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 SPSS to Compute the Regression Line

The More Predictors the Better? Maybe

Real-World Stats

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

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 SPSS to Perform Chi-Square Tests

Other Nonparametric Tests You Should Know About

Real-World Stats

Summary

Time to Practice

Chapter 18. 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

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

What You Will Learn in This Chapter

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

Appendix B

Appendix C

Appendix D

Appendix E

Appendix F

Appendix G

Appendix H

Appendix I

Glossary