Applied Multivariate Statistical Modeling

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2 STUDENTS

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

Course Curriculum

Introduction to multivariate statistical modeling Details 1:2:54
Introduction to multivariate statistical modeling I Details 59:37
Univariate descriptive statistics Details 1:1:34
Sampling distribution Details 1:1:37
Estimation Details 44:14
Estimation II Details 35:50
Hypothesis testing Details 59:12
Multivariate descriptive statistics Details 1:36
Multivariate descriptive statistics I Details 52:12
Multivariate normal distribution Details 57:33
Multivariate normal distribution I Details 58:30
Multivariate Inferential Statistics Details 1:1:11
Multivariate Inferential Statistics I Details 56:14
ANOVA (Analysis of Varianace) Details 56:40
Analysis of Variance (Contd.) Details 55:43
Multivariate Analysis of Variance (MANOVA) Details 59:27
MANOVA (Contd.) Details 59:23
Tutorial — ANOVA Details 58:34
Tutorial ANOVA I Details 52:40
MANOVA — Case Study II Details 1:2:51
Multiple Regression — Introduction Details 1:1:9
MLR — Sampling distribution of regression coefficients Details 59:56
MLR — Model adequacy tests Details 54:53
MLR — Test of assumptions Details 45:49
MLR — Model diagnostics Details 55:51
MLR — Case Study Details 1:2:49
Multivariate Linear Regression Details 1:6
Multivariate Linear Regression — Estimation Details 58:20
Multivariate Linear Regression — Model Adequacy tests I Details 59:11
Principal Component Analysis (PCA) Details 1:3:17
PCA — Model Adequacy & Interpretation Details 58:46
Regression Modeling using SPSS Details 1:4
Factor Analysis Details 1:3:5
Factor Analysis — Estimation & Model Adequacy testing I Details 1:2:14
Factor Analysis — Model Adequacy, rotation, factor scores & case study II Details 1:1:21
Cluster Analysis Details 57:34
Cluster Analysis I Details 1:1:3
Introduction to Structural Equation Modeling (SEM) Details 55:45
SEM – Measurement Model Details 1:50
SEM – Structural Model Details 1:1:14
Correspondence Analysis Details 58:36
Correspondence Analysis I Details 1:3:26

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