Foundation of behavioral statistics: an Insight based approach Bruce Thompson

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