Foundation of behavioral statistics: an Insight based approach
Bruce Thompson
- New York: The Guilford Press, 2006.
- 456p.
Introductory Terms and Concepts Definitions of Some Basic Terms Levels of Scale Some Experimental Design Considerations C Location Some Key Concepts Reflection Problems Reasonable Expectations for Statistics Location Concepts Three Classical Location Descriptive Statistics Four Criteria for Evaluating Statistics Two Robust Location Statistics 3 Dispersion Some Key Concepts Reflection Problems 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 Problems 4 Shape Two Shape Descriptive Statistics Normal Distributions Two Additional Univariate Graphics Some Key Concepts Reflection Problems 5 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 Problems 6 Statistical Significance Sampling Distributions Hypothesis Testing Properties of Sampling Distributions Standard Error/Sampling Error Test Statistics Statistical Precision and Power PCALCULATKD Some Key Concepts Reflection Problems 7 Practical Significance Effect Sizes Confidence Intervals Confidence Intervals for Effect Sizes Some Key Concepts Reflection Problems 8 Multiple Regression Analysis: Basic GLM Concepts Purposes of Regression Simple Linear Prediction Contents Case #1: Perfectly Uncorrelated Predictors Case #2: Correlated Predictors, No Suppressor Effects Case #3: Correlated Predictors, Suppressor Effects Present P Weights versus Structure Coefficients A Einal Comment on Collinearity Some Key Concepts Reflection Problems 9 A GLM Interpretation Rubric Do I Have Anything? Where Does My Something Originate? Stepwise Methods Invoking Some Alternative Models Some Key Concepts Reflection Problems I 0 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 Problems II Multiway and Other Alternative ANOVA Models Multiway Models Factorial versus Nonfactorial Analyses Fixed-, Random-, and Mixed-Effects Models Brief Comment on ANCOVA Some Key Concepts Reflection Problems 1 2 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 Problems 1 3 Some Logistic Models; Model Fitting in a Logistic Context Logistic Regression Loglinear Analysis Some Key Concepts Reflection Problems