Bruce Thompson 
Foundations of Behavioral Statistics [PDF ebook] 
An Insight-Based Approach

Preface1. Introductory Terms and Concepts            Definitions of Some Basic Terms            Levels of Scale            Some Experimental Design Considerations            Some Key Concepts            Reflection Problems2. Location            Reasonable Expectations for Statistics            Location Concepts            Three Classical Location Descriptive Statistics            Four Criteria for Evaluating Statistics            Two Robust Location Statistics            Some Key Concepts            Reflection Problems3. Dispersion            Quality of Location Descriptive Statistics            Important in Its Own Right             Measures of Score Spread            Variance            Situation-Specific Maximum Dispersion            Robust Dispersion Descriptive Statistics            Standardized Score World            Some Key Concepts            Reflection Problems4. Shape            Two Shape Descriptive Statistics            Normal Distributions            Two Additional Univariate Graphics            Some Key Concepts            Reflection Problems5. Bivariate Relationships            Pearson’s r            Three Features of r            Three Interpretation Contextual Factors            Psychometrics of the Pearson r            Spearman’s rho            Two Other r -Equivalent Correlation Coefficients            Bivariate Normality            Some Key Concepts            Reflection Problems6. Statistical Significance            Sampling Distributions            Hypothesis Testing            Properties of Sampling Distributions            Standard Error/Sampling Error            Test Statistics            Statistical Precision and Power            p CALCULATED            Some Key Concepts            Reflection Problems7. Practical Significance            Effect Sizes            Confidence Intervals            Confidence Intervals for Effect Sizes            Some Key Concepts            Reflection Problems8. Multiple Regression Analysis: Basic GLM Concepts            Purposes of Regression            Simple Linear Prediction            Case #1: Perfectly Uncorrelated Predictors Case #2: Correlated Predictors, No Suppressor   Effects Case #3: Correlated Predictors, Suppressor  Effects Present            b Weights versus Structure Coefficients            A Final Comment on Collinearity            Some Key Concepts            Reflection Problems9. A GLM Interpretation Rubric            Do I Have Anything?            Where Does My Something Originate?            Stepwise Methods            Invoking Some Alternative Models            Some Key Concepts            Reflection Problems10. One-way Analysis of Variance (ANOVA)            Experimentwise Type I Error            ANOVA Terminology            The Logic of Analysis of Variance            Practical and Statistical Significance            The ‘Homogeneity of Variance’ Assumption            Post Hoc Tests            Some Key Concepts            Reflection Problems11. Multiway and Alternative ANOVA Models            Multiway Models            Factorial versus Nonfactorial Analyses            Fixed-, Random-, and Mixed-Effects Models            Brief Comment on ANCOVA            Some Key Concepts            Reflection Problems12. The General Linear Model (GLM): ANOVA via Regression            Planned Contrasts            Trend/Polynomial Planned Contrasts            Repeated Measures ANOVA via Regression            GLM Lessons            Some Key Concepts            Reflection Problems13. Some Logistic Models: Model Fitting in a Logistic Context            Logistic Regression            Loglinear Analysis            Some Key Concepts            Reflection Problems Appendix: Scores (n = 100) with Near Normal Distributions

Bruce Thompson is Distinguished Professor of Educational Psychology and Distinguished Professor of Library Sciences, Texas A&M University, and Adjunct Professor of Family and Community Medicine, Baylor College of Medicine, Houston. He is the coeditor of the teaching, learning, and human development section of the American Educational Research Journal and past editor of Educational and Psychological Measurement, the series Advances in Social Science Methodology, and two other journals. He is the author or editor of 10 books, has written over 175 research articles, and has made contributions that have been influential in promoting greater emphasis on effect size reporting and interpretation, and improved understanding of score reliability.