图书简介

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

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