This text focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to help students better understand relevant data that affect their everyday lives.

Preface, Chapter 1: Why Statistics?, Part I: Descriptive Statistics, Chapter 2: Frequency Distributions and Percentiles, Chapter 3: Central Tendency and Variability, Chapter 4: z Scores and Normal Distributions, Part II: Introduction to Inferential Statistics, Chapter 5: Overview of Inferential Statistics, Chapter 6: Probability, Chapter 7: Sampling Distributions, Chapter 8: Logic of Hypothesis Testing, Chapter 9: Power, Chapter 10: Logic of Parameter Estimation, Part III: Applications of Inferential Statistics, Chapter 11: Inferences About Population Proportions Using the z Statistic, Chapter 12: Inferences About µ When s Is Unknown: The Single-sample t Test, Chapter 13: Comparing Two Populations: Independent Samples, Chapter 14: Random Sampling, Random Assignment, and Causality, Chapter 15: Comparing Two Populations: Dependent Samples, Chapter 16: Comparing Two Population Variances: The F Statistic, Chapter 17: Comparing Multiple Population Means: One-factor ANOVA, Chapter 18: Introduction to Factorial Designs, Chapter 19: Computational Methods for the Factorial ANOVA, Chapter 20: Describing Linear Relationships: Regression, Chapter 21: Measuring the Strength of Linear Relationships Correlation, Chapter 22: Inferences From Nominal Data: The ¿ 2 Statistic, Glossary of Symbols, Tables, Appendix A. Variables From the Stop Smoking Study, Appendix B. Variables From the Wisconsin Maternity Leave and Health Project and the Wisconsin Study of Families and Work, Answers to Selected Exercises, Index