Sl.No | Chapter Name | MP4 Download |
---|---|---|
1 | Lecture 01: Introduction to Multivariate Statistical Modeling | Download |
2 | Lecture 02: Introduction to Multivariate Statistical Modeling: Data types, models, and modeling " | Download |
3 | Lecture 03: Statistical approaches to model building | Download |
4 | Lecture 04: Statistical approaches to model building (Contd) | Download |
5 | Lecture 05: Univariate Descriptive Statistics " | Download |
6 | Lecture 06: Univariate Descriptive Statistics (Contd) " | Download |
7 | Lecture 07: Normal Distribution and Chi-squared Distribution | Download |
8 | Lecture 08: t-distribution, F-distribution, and Central Limit Theorem | Download |
9 | Lecture 09: Univariate Inferential Statistics: Estimation | Download |
10 | Lecture 10: Univariate Inferential Statistics: Estimation(Contd) | Download |
11 | Lecture 11: Univariate Inferential Statistics: Hypothesis Testing | Download |
12 | Lecture 12: Hypothesis Testing(contd): Decision Making Scenarios | Download |
13 | Lecture 13: Multivariate Descriptive Statistics: Mean Vector | Download |
14 | Lecture 14: Multivariate Descriptive Statistics: Covariance Matrix | Download |
15 | Lecture 15: Multivariate Descriptive Statistics: Correlation Matrix | Download |
16 | Lecture 16: Multivariate Descriptive Statistics: Relationship between correlation and covariance matrices | Download |
17 | Lecture 17: Multivariate Normal Distribution | Download |
18 | Lecture 18: Multivariate Normal Distribution(Contd) | Download |
19 | Lecture 19: Multivariate Normal Distribution (Contd): Geometrical Interpretation | Download |
20 | Lecture 20: Multivariate Normal Distribution (Contd): Examining data for multivariate normal distribution | Download |
21 | Lecture 21: Multivariate Inferential Statistics: Basics and Hotelling T - square statistic | Download |
22 | Lecture 22: Multivariate Inferential Statistics: Confidence Region | Download |
23 | Lecture 23: Multivariate Inferential Statistics: Simultaneous confidence interval and Hypothesis testing | Download |
24 | Lecture 24: Multivariate Inferential Statistics: Hypothesis testing for equality of two population mean vectors " | Download |
25 | Lecture 25: Analysis of Variance (ANOVA) | Download |
26 | Lecture 26: Analysis of Variance (ANOVA): Decomposition of Total sum of squares | Download |
27 | Lecture 27: Analysis of Variance (ANOVA): Estimation of Parameters and Model Adequacy tests | Download |
28 | Lecture 28: Two-way and Three-way Analysis of Variance (ANOVA) | Download |
29 | Lecture 29: Tutorial ANOVA | Download |
30 | Lecture 30: Tutorial ANOVA (Contd) | Download |
31 | Lecture 31: Multivariate Analysis of Variance (MANOVA): Conceptual Model | Download |
32 | Lecture 32: Multivariate Analysis of Variance (MANOVA): Assumptions and Decomposition of total sum square and cross products (SSCP) | Download |
33 | Lecture 33: Multivariate Analysis of Variance (MANOVA): Decomposition of total sum square and cross products (SSCP)(contd) | Download |
34 | Lecture 34: Multivariate Analysis of Variance (MANOVA): Estimation and Hypothesis testing | Download |
35 | Lecture 35: MANOVA Case Study | Download |
36 | Lecture 36: Multiple Linear Regression: Introduction | Download |
37 | Lecture 37: Multiple Linear Regression: Assumptions and Estimation of model parameters | Download |
38 | Lecture 38: Multiple Linear Regression: Sampling Distribution of parameter estimates | Download |
39 | Lecture 39: Multiple Linear Regression: Sampling Distribution of parameter estimates (contd) | Download |
40 | Lecture 40: Multiple Linear Regression: Model Adequacy Tests | Download |
41 | Lecture 41: Multiple Linear Regression: Model Adequacy Tests(contd) | Download |
42 | Lecture 42: Multiple Linear Regression: Test of Assumptions | Download |
43 | Lecture 43: MLR-Model diagnostics | Download |
44 | Lecture 44: MLR-case study | Download |
45 | Lecture 45: Multivariate Linear Regression: conceptual model and assumptions | Download |
46 | Lecture 46: Multivariate Linear Regression: Estimation of parameters | Download |
47 | Lecture 47: Multivariate Linear Regression: Estimation of parameters (contd) | Download |
48 | Lecture 48: Multiple Linear Regression: Sampling Distribution of parameter estimates | Download |
49 | Lecture 49: Multivariate Linear Regression: Model Adequacy Tests | Download |
50 | Lecture 50: Multiple Linear Regression: Model Adequacy Tests(contd) | Download |
51 | Lecture 51: Regression modeling using SPSS | Download |
52 | Lecture 52: Principal Component Analysis (PCA): Conceptual Model | Download |
53 | Lecture 53: Principal Component Analysis (PCA): Extraction of Principal components (PCs) | Download |
54 | Lecture 54: Principal Component Analysis (PCA): Model Adequacy and Interpretation | Download |
55 | Lecture 55: Principal Component Analysis (PCA): Model Adequacy and Interpretation (contd) " | Download |
56 | Lecture 56: Factor Analysis: Basics and Orthogonal factor models | Download |
57 | Lecture 57: Factor Analysis: Types of models and key questions | Download |
58 | Lecture 58: Factor Analysis: Parameter Estimation | Download |
59 | Lecture 59: Factor Analysis: Parameter Estimation(contd) | Download |
60 | Lecture 60: Factor Analysis: Model Adequacy tests and factor rotation | Download |
61 | Lecture 61: Factor Analysis: Factor scores and case study | Download |
Sl.No | Chapter Name | English |
---|---|---|
1 | Lecture 01: Introduction to Multivariate Statistical Modeling | Download To be verified |
2 | Lecture 02: Introduction to Multivariate Statistical Modeling: Data types, models, and modeling " | Download To be verified |
3 | Lecture 03: Statistical approaches to model building | Download To be verified |
4 | Lecture 04: Statistical approaches to model building (Contd) | Download To be verified |
5 | Lecture 05: Univariate Descriptive Statistics " | Download To be verified |
6 | Lecture 06: Univariate Descriptive Statistics (Contd) " | Download To be verified |
7 | Lecture 07: Normal Distribution and Chi-squared Distribution | Download To be verified |
8 | Lecture 08: t-distribution, F-distribution, and Central Limit Theorem | Download To be verified |
9 | Lecture 09: Univariate Inferential Statistics: Estimation | Download To be verified |
10 | Lecture 10: Univariate Inferential Statistics: Estimation(Contd) | Download To be verified |
11 | Lecture 11: Univariate Inferential Statistics: Hypothesis Testing | Download To be verified |
12 | Lecture 12: Hypothesis Testing(contd): Decision Making Scenarios | Download To be verified |
13 | Lecture 13: Multivariate Descriptive Statistics: Mean Vector | Download To be verified |
14 | Lecture 14: Multivariate Descriptive Statistics: Covariance Matrix | Download To be verified |
15 | Lecture 15: Multivariate Descriptive Statistics: Correlation Matrix | Download To be verified |
16 | Lecture 16: Multivariate Descriptive Statistics: Relationship between correlation and covariance matrices | Download To be verified |
17 | Lecture 17: Multivariate Normal Distribution | Download To be verified |
18 | Lecture 18: Multivariate Normal Distribution(Contd) | Download To be verified |
19 | Lecture 19: Multivariate Normal Distribution (Contd): Geometrical Interpretation | Download To be verified |
20 | Lecture 20: Multivariate Normal Distribution (Contd): Examining data for multivariate normal distribution | Download To be verified |
21 | Lecture 21: Multivariate Inferential Statistics: Basics and Hotelling T - square statistic | Download To be verified |
22 | Lecture 22: Multivariate Inferential Statistics: Confidence Region | Download To be verified |
23 | Lecture 23: Multivariate Inferential Statistics: Simultaneous confidence interval and Hypothesis testing | Download To be verified |
24 | Lecture 24: Multivariate Inferential Statistics: Hypothesis testing for equality of two population mean vectors " | Download To be verified |
25 | Lecture 25: Analysis of Variance (ANOVA) | Download To be verified |
26 | Lecture 26: Analysis of Variance (ANOVA): Decomposition of Total sum of squares | Download To be verified |
27 | Lecture 27: Analysis of Variance (ANOVA): Estimation of Parameters and Model Adequacy tests | Download To be verified |
28 | Lecture 28: Two-way and Three-way Analysis of Variance (ANOVA) | Download To be verified |
29 | Lecture 29: Tutorial ANOVA | PDF unavailable |
30 | Lecture 30: Tutorial ANOVA (Contd) | PDF unavailable |
31 | Lecture 31: Multivariate Analysis of Variance (MANOVA): Conceptual Model | PDF unavailable |
32 | Lecture 32: Multivariate Analysis of Variance (MANOVA): Assumptions and Decomposition of total sum square and cross products (SSCP) | PDF unavailable |
33 | Lecture 33: Multivariate Analysis of Variance (MANOVA): Decomposition of total sum square and cross products (SSCP)(contd) | PDF unavailable |
34 | Lecture 34: Multivariate Analysis of Variance (MANOVA): Estimation and Hypothesis testing | PDF unavailable |
35 | Lecture 35: MANOVA Case Study | PDF unavailable |
36 | Lecture 36: Multiple Linear Regression: Introduction | PDF unavailable |
37 | Lecture 37: Multiple Linear Regression: Assumptions and Estimation of model parameters | PDF unavailable |
38 | Lecture 38: Multiple Linear Regression: Sampling Distribution of parameter estimates | PDF unavailable |
39 | Lecture 39: Multiple Linear Regression: Sampling Distribution of parameter estimates (contd) | PDF unavailable |
40 | Lecture 40: Multiple Linear Regression: Model Adequacy Tests | PDF unavailable |
41 | Lecture 41: Multiple Linear Regression: Model Adequacy Tests(contd) | PDF unavailable |
42 | Lecture 42: Multiple Linear Regression: Test of Assumptions | PDF unavailable |
43 | Lecture 43: MLR-Model diagnostics | PDF unavailable |
44 | Lecture 44: MLR-case study | PDF unavailable |
45 | Lecture 45: Multivariate Linear Regression: conceptual model and assumptions | PDF unavailable |
46 | Lecture 46: Multivariate Linear Regression: Estimation of parameters | PDF unavailable |
47 | Lecture 47: Multivariate Linear Regression: Estimation of parameters (contd) | PDF unavailable |
48 | Lecture 48: Multiple Linear Regression: Sampling Distribution of parameter estimates | PDF unavailable |
49 | Lecture 49: Multivariate Linear Regression: Model Adequacy Tests | PDF unavailable |
50 | Lecture 50: Multiple Linear Regression: Model Adequacy Tests(contd) | PDF unavailable |
51 | Lecture 51: Regression modeling using SPSS | PDF unavailable |
52 | Lecture 52: Principal Component Analysis (PCA): Conceptual Model | PDF unavailable |
53 | Lecture 53: Principal Component Analysis (PCA): Extraction of Principal components (PCs) | PDF unavailable |
54 | Lecture 54: Principal Component Analysis (PCA): Model Adequacy and Interpretation | PDF unavailable |
55 | Lecture 55: Principal Component Analysis (PCA): Model Adequacy and Interpretation (contd) " | PDF unavailable |
56 | Lecture 56: Factor Analysis: Basics and Orthogonal factor models | PDF unavailable |
57 | Lecture 57: Factor Analysis: Types of models and key questions | PDF unavailable |
58 | Lecture 58: Factor Analysis: Parameter Estimation | PDF unavailable |
59 | Lecture 59: Factor Analysis: Parameter Estimation(contd) | PDF unavailable |
60 | Lecture 60: Factor Analysis: Model Adequacy tests and factor rotation | PDF unavailable |
61 | Lecture 61: Factor Analysis: Factor scores and case study | PDF unavailable |
Sl.No | Language | Book link |
---|---|---|
1 | English | Not Available |
2 | Bengali | Not Available |
3 | Gujarati | Not Available |
4 | Hindi | Not Available |
5 | Kannada | Not Available |
6 | Malayalam | Not Available |
7 | Marathi | Not Available |
8 | Tamil | Not Available |
9 | Telugu | Not Available |