Preface Acknowledgements 1. Prelude: Why Do I Need to Learn Statistics? -The Nature of Findings and Facts in the Behavioral Sciences - Statistical Significance and Effect Size - Descriptive and Inferential Statistics - A Conceptual Approach to Teaching and Learning Statistics - The Nature of this Book - How to Approach this Class and What You Should Get Out of It - Key Terms 2. Describing a Single Variable - Variables, Values, and Scores - Types of Variables - Describing Scores for a Single Variable - Indices of Central Tendency - Indices of Variability (and the Sheer Beauty of Standard Deviation!) - Rounding - Describing Frequencies of Values for a Single Variable - Representing Frequency Data Graphically - Describing Data for a Categorical Variable - A Real Research Example - Summary - Key Terms 3. Standardized Scores - When a Z-Score Equals 0, the Raw Score It Corresponds to Must Equal the Mean - Verbal Scores for the Madupistan Aptitude Measure - Quantitative Scores for the Madupistan Aptitude Measure - Every Raw Score for Any Variable Corresponds to a Particular Z-Score - Computing Z-Scores for All Students for the Madupistan Verbal Test - Computing Raw Scores from Z-Scores - Comparing Your GPA of 3.10 from Solid State University with Pat''s GPA of 1.95 from Advanced Technical University - Each Z-Score for Any Variable Corresponds to a Particular Raw Score - Converting Z-Scores to Raw Scores (The Dorm Resident Example) - A Real Research Example - Summary - Key Terms 4. Correlation - Correlations Are Summaries - Representing a Correlation Graphically - Representing a Correlation Mathematically - Return to Madupistan - Correlation Does Not Imply Causation - A Real Research Example - Summary - Key Terms 5. Statistical Prediction and Regression - Standardized Regression - Predicting Scores on Y with Different Amounts of Information - Beta Weight - Unstandardized Regression Equation - The Regression Line - Quantitatively Estimating the Predictive Power of Your Regression Model - Interpreting r2 - A Real Research Example - Conclusion - Key Terms 6.

The Basic Elements of Hypothesis Testing - The Basic Elements of Inferential Statistics - The Normal Distribution - A Real Research Example - Summary - Key Terms 7. Introduction to Hypothesis Testing - The Basic Rationale of Hypothesis Testing - Understanding the Broader Population of Interest - Population versus Sample Parameters - The Five Basic Steps of Hypothesis Testing - A Real Research Example - Summary - Key Terms 8. Hypothesis Testing if N > 1 - The Distribution of Means - Steps in Hypothesis Testing if N > 1 - Confidence Intervals - Real Research Example - Summary - Key Terms 9. Statistical Power - What Is Statistical Power? - An Example of Statistical Power - Factors that Affect Statistical Power - A Real Research Example - Summary - Key Terms 10. t-tests (One-Sample and Within-Groups) - One-Sample t-test - Steps for Hypothesis Testing with a One-Sample t-test - Here Are Some Simple Rules to Determine the Sign of tcrit with a One-Sample t-Test - Computing Effect Size with a One-Sample t-Test - How the t-Test Is Biased Against Small Samples - The Within-Group t-Test - Steps in Computing the Within-Group t-Test - Computing Effect Size with a Within-Group t-test - A Real Research Example - Summary - Key Terms 11. The Between-Groups t-test - The Elements of the Between-Groups t-test - Effect Size with the Between-Groups t-test - Another Example - Real Research Example - Summary - Key Terms 12. Analysis of Variance - ANOVA as a Signal-Detection Statistic - An Example of the One-Way ANOVA - What Can and Cannot Be Inferred from ANOVA (The Importance of Follow-Up Tests) - Estimating Effect Size with the One-Way ANOVA - Real Research Example - Summary - Key Terms 13. Chi Square and Hypothesis-Testing with Categorical Variables - Chi Square Test of Goodness of Fit - Steps in Hypothesis Testing with Chi Square Goodness of Fit - What Can and Cannot Be Inferred from a Significant Chi Square - Chi Square Goodness of Fit Testing for Equality across Categories - Chi Square Test of Independence - Real Research Example - Summary - Key Terms Appendix A: Cumulative Standardized Normal Distribution Appendix B: t Distribution: Critical Values of t Appendix C: F Distribution: Critical Values of F Appendix D: Chi Square Distribution: Critical Values of ?2 (Chi Squared) Distribution: Critical Values of ?2 Appendix E: Advanced Statistics to Be Aware of - Advanced Forms of ANOVA - Summary - Key Terms Appendix F: Using SPSS - Activity 1: SPSS Data Entry Lab - Activity 2: Working with SPSS Syntax Files - Syntax Files, Recoding Variables, Compute Statements, Out Files, and the Computation of Variables in SPSS - Recoding Variables - Computing New Variables - Output Files - Example: How to Recode Items for the Jealousy Data and Compute Composite Variables - Activity 3: Descriptive Statistics - Frequencies, Descriptives, and Histograms - Frequencies, Descriptives, and Histograms for Data Measured in Class - The Continuous Variable - The Categorical Variable - Activity 4: Correlations - Activity 5: Regression - Activity 6: t-tests - Independent Samples Test - Activity 7: ANOVA with SPSS - Post Hoc Tests - Homogeneous Subsets - Activity 8: Factorial ANOVA - Recomputing Variables so as to Be Able to Conduct a One-Way ANOVA to Examine Specific Differences Between Means - Activity 9: Chi Square - Crosstabs Glossary References Index.