Applied Multivariate Statistical Modeling

Overview

Background - Introduction to multivariate statistical modeling : Basic univariate statistics - Univariate descriptive statistics - Sampling distribution - Estimation - Hypothesis testing - Basic multivariate statistics - Multivariate descriptive statistics - Multivariate normal distribution - Multivariate Inferential statistics

Multivariate models : Analysis of variance (ANOVA) - Multivariate analysis of variance (MANOVA) - Tutorial: ANOVA - Case study: MANOVA - Multiple linear regression (MLR): Introduction - MLR: Sampling distribution of regression coefficients - MLR: Model adequacy tests - MLR: Test of assumptions - MLR: Model diagnostics - MLR: Case study - Multivariate linear regression (MvLR): Introduction - MvLR: Estimation - MvLR: Model adequacy tests - Regression modeling using SPSS - Principle component analysis (PCA): Introduction - PCA: Model adequacy and interpretation - Factor analysis (FA): Introduction - FA: Estimation and model adequacy testing - FA: Rotation, factor scores, and case study - Cluster analysis (CA) - Introduction to structural equation modeling (SEM) - Correspondence analysis