# Applied Multivariate Statistical Modeling

0( 0 REVIEWS )
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

## N.A

ratings
• 5 stars0
• 4 stars0
• 3 stars0
• 2 stars0
• 1 stars0

No Reviews found for this course.

• FREE
• UNLIMITED ACCESS