Fundamental Statistics for the Social and Behavioral Sciences 2/e

Howard T. Tokunaga is Professor of Psychology at San Jose State University, where he serves as Coordinator of the MS Program in Industrial/Organizational (I/O) Psychology and teaches undergraduate and graduate courses in statistics, research methods, and I/O psychology. He received his bachelor's degree in psychology at UC Santa Cruz and his PhD in psychology at UC Berkeley. In addition to his teaching, he has consulted with a number of public-sector and private-sector organizations on a wide variety of management and human resource issues. He is coauthor (with G. Keppel) of Introduction to Design and Analysis: A Student's Handbook.

About the Author Preface to the Second Edition Preface to the First Edition Acknowledgments Companion Site Chapter 1. Introduction to Statistics 1.1 What Is Statistics? 1.2 Why Learn Statistics? 1.3 Introduction to the Stages of the Research Process 1.4 Plan of the Book 1.5 Looking Ahead 1.6 Summary 1.7 Important Terms 1.8 Exercises Chapter 2. Examining Data: Tables and Figures 2.1 An Example From the Research: Winning the Lottery 2.2 Why Examine Data? 2.3 Examining Data Using Tables 2.4 Grouped Frequency Distribution Tables 2.5 Examining Data Using Figures 2.6 Examining Data: Describing Distributions 2.7 Looking Ahead 2.8 Summary 2.9 Important Terms 2.10 Formulas Introduced in This Chapter 2.11 Using IBM SPSS Software 2.12 Exercises Chapter 3. Measures of Central Tendency 3.1 An Example From the Research: The 10% Myth 3.2 Understanding Central Tendency 3.3 The Mode 3.4 The Median 3.5 The Mean 3.6 Comparison of the Mode, Median, and Mean 3.7 Measures of Central Tendency: Drawing Conclusions 3.8 Looking Ahead 3.9 Summary 3.10 Important Terms 3.11 Formulas Introduced in This Chapter 3.12 Exercises Chapter 4. Measures of Variability 4.1 An Example From the Research: How Many "Sometimes" in an "Always"? 4.2 Understanding Variability 4.3 The Range 4.4 The Interquartile Range 4.5 The Variance (s2) 4.6 The Standard Deviation (s) 4.7 Measures of Variability for Populations 4.8 Measures of Variability for Nominal Variables 4.9 Measures of Variability: Drawing Conclusions 4.10 Looking Ahead 4.11 Summary 4.12 Important Terms 4.13 Formulas Introduced in This Chapter 4.14 Using SPSS 4.15 Exercises Chapter 5. Normal Distributions 5.1 Example: SAT Scores 5.2 Normal Distributions 5.3 The Standard Normal Distribution 5.4 Applying z-Scores to Normal Distributions 5.5 Standardizing Frequency Distributions 5.6 Looking Ahead 5.7 Summary 5.8 Important Terms 5.9 Formulas Introduced in This Chapter 5.10 Exercises Chapter 6. Probability and Introduction to Hypothesis Testing 6.1 A Brief Introduction to Probability 6.2 Example: Making Heads or Tails of the Super Bowl 6.3 Introduction to Hypothesis Testing 6.4 Issues Related to Hypothesis Testing: An Introduction 6.5 Looking Ahead 6.6 Summary 6.7 Important Terms 6.8 Formulas Introduced in This Chapter 6.9 Exercises Chapter 7. Testing One Sample Mean 7.1 An Example From the Research: Do You Read Me? 7.2 The Sampling Distribution of the Mean 7.3 Inferential Statistics: Testing One Sample Mean (s Known) 7.4 A Second Example From the Research: Unique Invulnerability 7.5 Introduction to the t-Distribution 7.6 Inferential Statistics: Testing One Sample Mean (s Not Known) 7.7 Factors Affecting the Decision About the Null Hypothesis 7.8 Looking Ahead 7.9 Summary 7.10 Important Terms 7.11 Formulas Introduced in This Chapter 7.12 Using SPSS 7.13 Exercises Chapter 8. Estimating the Mean of a Population 8.1 An Example From the Research: Salary Survey 8.2 Introduction to the Confidence Interval for the Mean 8.3 The Confidence Interval for the Mean (s Not Known) 8.4 The Confidence Interval for the Mean (s Known) 8.5 Factors Affecting the Width of the Confidence Interval for the Mean 8.6 Interval Estimation and Hypothesis Testing 8.7 Looking Ahead 8.8 Summary 8.9 Important Terms 8.10 Formulas Introduced in This Chapter 8.11 Using SPSS 8.12 Exercises Chapter 9. Testing the Difference Between Two Means 9.1 An Example From the Research: You Can Just Wait 9.2 The Sampling Distribution of the Difference 9.3 Inferential Statistics: Testing the Difference Between Two Sample Means 9.4 Inferential Statistics: Testing the Difference Between Two Sample Means (Unequal Sample Sizes) 9.5 Inferential Statistics: Testing the Difference Between Paired Means 9.6 Looking Ahead 9.7 Summary 9.8 Important Terms 9.9 Formulas Introduced in This Chapter 9.10 Using SPSS 9.11 Exercises Chapter 10. Errors in Hypothesis Testing, Statistical Power, and Effect Size 10.1 Hypothesis Testing vs. Criminal Trials 10.2 An Example From the Research: Truth or Consequences 10.3 Two Errors in Hypothesis Testing: Type I and Type II Error 10.4 Controlling Type I and Type II Error 10.5 Measures of Effect Size 10.6 Looking Ahead 10.7 Summary 10.8 Important Terms 10.9 Formulas Introduced in This Chapter 10.10 Exercises Chapter 11. One-Way Analysis of Variance (ANOVA) 11.1 An Example From the Research: It's Your Move 11.2 Introduction to Analysis of Variance (ANOVA) 11.3 Inferential Statistics: One-Way Analysis of Variance (ANOVA) 11.4 A Second Example: The Parking Lot Study Revisited 11.5 Analytical Comparisons Within the One-Way ANOVA 11.6 Looking Ahead 11.7 Summary 11.8 Important Terms 11.9 Formulas Introduced in This Chapter 11.10 Using SPSS 11.11 Exercises Chapter 12. Two-Way Analysis of Variance (ANOVA) 12.1 An Example From the Research: Vote-or Else! 12.2 Introduction to Factorial Research Designs 12.3 The Two-Factor (A x B) Research Design 12.4 Introduction to Analysis of Variance (ANOVA) for the Two-Factor Research Design 12.5 Inferential Statistics: Two-Way Analysis of Variance (ANOVA) 12.6 Investigating a Significant A x B Interaction Effect: Analysis of Simple Effects 12.7 Looking Ahead 12.8 Summary 12.9 Important Terms 12.10 Formulas Introduced in This Chapter 12.11 Using SPSS 12.12 Exercises Chapter 13. Correlation 13.1 An Example From the Research: It's Good for You! 13.2 Introduction to the Concept of Correlation 13.3 Inferential Statistics: Pearson Correlation Coefficient 13.4 Correlating Two Sets of Ranks: The Spearman Rank-Order Correlation 13.5 Correlational Statistics vs. Correlational Research 13.6 Looking Ahead 13.7 Summary 13.8 Important Terms 13.9 Formulas Introduced in This Chapter 13.10 Using SPSS 13.11 Exercises Chapter 14. Linear Regression and Multiple Correlation 14.1 Predicting One Variable From Another: Linear Regression 14.2 Correlation With Two or More Predictors: Introduction to Multiple Correlation and Regression 14.3 Looking Ahead 14.4 Summary 14.5 Important Terms 14.6 Formulas Introduced in This Chapter 14.7 Using SPSS 14.8 Exercises Chapter 15. Chi-Square 15.1 An Example From the Research (One Categorical Variable): Are You My Type? 15.2 Introduction to the Chi-Square Statistic 15.3 Inferential Statistic: Chi-Square Goodness-of-Fit Test 15.4 An Example From the Research (Two Categorical Variables): Seeing Red 15.5 Inferential Statistic: Chi-Square Test of Independence 15.6 Parametric and Nonparametric Statistical Tests 15.7 Looking Ahead 15.8 Summary 15.9 Important Terms 15.10 Formulas Introduced in This Chapter 15.11 Using SPSS 15.12 Exercises Tables Appendix: Review of Basic Mathematics Glossary References Index

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