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Assignment 1Assignment 1


Sl.No Chapter Name MP4 Download
1Lecture 01: Introduction to Multivariate Statistical ModelingDownload
2Lecture 02: Introduction to Multivariate Statistical Modeling: Data types, models, and modeling "Download
3Lecture 03: Statistical approaches to model buildingDownload
4Lecture 04: Statistical approaches to model building (Contd)Download
5Lecture 05: Univariate Descriptive Statistics "Download
6Lecture 06: Univariate Descriptive Statistics (Contd) "Download
7Lecture 07: Normal Distribution and Chi-squared DistributionDownload
8Lecture 08: t-distribution, F-distribution, and Central Limit TheoremDownload
9Lecture 09: Univariate Inferential Statistics: EstimationDownload
10Lecture 10: Univariate Inferential Statistics: Estimation(Contd)Download
11Lecture 11: Univariate Inferential Statistics: Hypothesis TestingDownload
12Lecture 12: Hypothesis Testing(contd): Decision Making ScenariosDownload
13Lecture 13: Multivariate Descriptive Statistics: Mean VectorDownload
14Lecture 14: Multivariate Descriptive Statistics: Covariance MatrixDownload
15Lecture 15: Multivariate Descriptive Statistics: Correlation MatrixDownload
16Lecture 16: Multivariate Descriptive Statistics: Relationship between correlation and covariance matricesDownload
17Lecture 17: Multivariate Normal DistributionDownload
18Lecture 18: Multivariate Normal Distribution(Contd)Download
19Lecture 19: Multivariate Normal Distribution (Contd): Geometrical InterpretationDownload
20Lecture 20: Multivariate Normal Distribution (Contd): Examining data for multivariate normal distributionDownload
21Lecture 21: Multivariate Inferential Statistics: Basics and Hotelling T - square statisticDownload
22Lecture 22: Multivariate Inferential Statistics: Confidence RegionDownload
23Lecture 23: Multivariate Inferential Statistics: Simultaneous confidence interval and Hypothesis testingDownload
24Lecture 24: Multivariate Inferential Statistics: Hypothesis testing for equality of two population mean vectors "Download
25Lecture 25: Analysis of Variance (ANOVA)Download
26Lecture 26: Analysis of Variance (ANOVA): Decomposition of Total sum of squaresDownload
27Lecture 27: Analysis of Variance (ANOVA): Estimation of Parameters and Model Adequacy testsDownload
28Lecture 28: Two-way and Three-way Analysis of Variance (ANOVA)Download
29Lecture 29: Tutorial ANOVADownload
30Lecture 30: Tutorial ANOVA (Contd)Download
31Lecture 31: Multivariate Analysis of Variance (MANOVA): Conceptual ModelDownload
32Lecture 32: Multivariate Analysis of Variance (MANOVA): Assumptions and Decomposition of total sum square and cross products (SSCP)Download
33Lecture 33: Multivariate Analysis of Variance (MANOVA): Decomposition of total sum square and cross products (SSCP)(contd)Download
34Lecture 34: Multivariate Analysis of Variance (MANOVA): Estimation and Hypothesis testingDownload
35Lecture 35: MANOVA Case StudyDownload
36Lecture 36: Multiple Linear Regression: IntroductionDownload
37Lecture 37: Multiple Linear Regression: Assumptions and Estimation of model parametersDownload
38Lecture 38: Multiple Linear Regression: Sampling Distribution of parameter estimatesDownload
39Lecture 39: Multiple Linear Regression: Sampling Distribution of parameter estimates (contd)Download
40Lecture 40: Multiple Linear Regression: Model Adequacy TestsDownload
41Lecture 41: Multiple Linear Regression: Model Adequacy Tests(contd)Download
42Lecture 42: Multiple Linear Regression: Test of AssumptionsDownload
43Lecture 43: MLR-Model diagnosticsDownload
44Lecture 44: MLR-case studyDownload
45Lecture 45: Multivariate Linear Regression: conceptual model and assumptionsDownload
46Lecture 46: Multivariate Linear Regression: Estimation of parametersDownload
47Lecture 47: Multivariate Linear Regression: Estimation of parameters (contd)Download
48Lecture 48: Multiple Linear Regression: Sampling Distribution of parameter estimatesDownload
49Lecture 49: Multivariate Linear Regression: Model Adequacy TestsDownload
50Lecture 50: Multiple Linear Regression: Model Adequacy Tests(contd)Download
51Lecture 51: Regression modeling using SPSSDownload
52Lecture 52: Principal Component Analysis (PCA): Conceptual ModelDownload
53Lecture 53: Principal Component Analysis (PCA): Extraction of Principal components (PCs)Download
54Lecture 54: Principal Component Analysis (PCA): Model Adequacy and InterpretationDownload
55Lecture 55: Principal Component Analysis (PCA): Model Adequacy and Interpretation (contd) "Download
56Lecture 56: Factor Analysis: Basics and Orthogonal factor modelsDownload
57Lecture 57: Factor Analysis: Types of models and key questionsDownload
58Lecture 58: Factor Analysis: Parameter EstimationDownload
59Lecture 59: Factor Analysis: Parameter Estimation(contd)Download
60Lecture 60: Factor Analysis: Model Adequacy tests and factor rotationDownload
61Lecture 61: Factor Analysis: Factor scores and case studyDownload

Sl.No Chapter Name English
1Lecture 01: Introduction to Multivariate Statistical ModelingDownload
To be verified
2Lecture 02: Introduction to Multivariate Statistical Modeling: Data types, models, and modeling "Download
To be verified
3Lecture 03: Statistical approaches to model buildingDownload
To be verified
4Lecture 04: Statistical approaches to model building (Contd)Download
To be verified
5Lecture 05: Univariate Descriptive Statistics "Download
To be verified
6Lecture 06: Univariate Descriptive Statistics (Contd) "Download
To be verified
7Lecture 07: Normal Distribution and Chi-squared DistributionDownload
To be verified
8Lecture 08: t-distribution, F-distribution, and Central Limit TheoremDownload
To be verified
9Lecture 09: Univariate Inferential Statistics: EstimationDownload
To be verified
10Lecture 10: Univariate Inferential Statistics: Estimation(Contd)Download
To be verified
11Lecture 11: Univariate Inferential Statistics: Hypothesis TestingDownload
To be verified
12Lecture 12: Hypothesis Testing(contd): Decision Making ScenariosDownload
To be verified
13Lecture 13: Multivariate Descriptive Statistics: Mean VectorDownload
To be verified
14Lecture 14: Multivariate Descriptive Statistics: Covariance MatrixDownload
To be verified
15Lecture 15: Multivariate Descriptive Statistics: Correlation MatrixDownload
To be verified
16Lecture 16: Multivariate Descriptive Statistics: Relationship between correlation and covariance matricesDownload
To be verified
17Lecture 17: Multivariate Normal DistributionDownload
To be verified
18Lecture 18: Multivariate Normal Distribution(Contd)Download
To be verified
19Lecture 19: Multivariate Normal Distribution (Contd): Geometrical InterpretationDownload
To be verified
20Lecture 20: Multivariate Normal Distribution (Contd): Examining data for multivariate normal distributionDownload
To be verified
21Lecture 21: Multivariate Inferential Statistics: Basics and Hotelling T - square statisticDownload
To be verified
22Lecture 22: Multivariate Inferential Statistics: Confidence RegionDownload
To be verified
23Lecture 23: Multivariate Inferential Statistics: Simultaneous confidence interval and Hypothesis testingDownload
To be verified
24Lecture 24: Multivariate Inferential Statistics: Hypothesis testing for equality of two population mean vectors "Download
To be verified
25Lecture 25: Analysis of Variance (ANOVA)Download
To be verified
26Lecture 26: Analysis of Variance (ANOVA): Decomposition of Total sum of squaresDownload
To be verified
27Lecture 27: Analysis of Variance (ANOVA): Estimation of Parameters and Model Adequacy testsDownload
To be verified
28Lecture 28: Two-way and Three-way Analysis of Variance (ANOVA)Download
To be verified
29Lecture 29: Tutorial ANOVAPDF unavailable
30Lecture 30: Tutorial ANOVA (Contd)PDF unavailable
31Lecture 31: Multivariate Analysis of Variance (MANOVA): Conceptual ModelPDF unavailable
32Lecture 32: Multivariate Analysis of Variance (MANOVA): Assumptions and Decomposition of total sum square and cross products (SSCP)PDF unavailable
33Lecture 33: Multivariate Analysis of Variance (MANOVA): Decomposition of total sum square and cross products (SSCP)(contd)PDF unavailable
34Lecture 34: Multivariate Analysis of Variance (MANOVA): Estimation and Hypothesis testingPDF unavailable
35Lecture 35: MANOVA Case StudyPDF unavailable
36Lecture 36: Multiple Linear Regression: IntroductionPDF unavailable
37Lecture 37: Multiple Linear Regression: Assumptions and Estimation of model parametersPDF unavailable
38Lecture 38: Multiple Linear Regression: Sampling Distribution of parameter estimatesPDF unavailable
39Lecture 39: Multiple Linear Regression: Sampling Distribution of parameter estimates (contd)PDF unavailable
40Lecture 40: Multiple Linear Regression: Model Adequacy TestsPDF unavailable
41Lecture 41: Multiple Linear Regression: Model Adequacy Tests(contd)PDF unavailable
42Lecture 42: Multiple Linear Regression: Test of AssumptionsPDF unavailable
43Lecture 43: MLR-Model diagnosticsPDF unavailable
44Lecture 44: MLR-case studyPDF unavailable
45Lecture 45: Multivariate Linear Regression: conceptual model and assumptionsPDF unavailable
46Lecture 46: Multivariate Linear Regression: Estimation of parametersPDF unavailable
47Lecture 47: Multivariate Linear Regression: Estimation of parameters (contd)PDF unavailable
48Lecture 48: Multiple Linear Regression: Sampling Distribution of parameter estimatesPDF unavailable
49Lecture 49: Multivariate Linear Regression: Model Adequacy TestsPDF unavailable
50Lecture 50: Multiple Linear Regression: Model Adequacy Tests(contd)PDF unavailable
51Lecture 51: Regression modeling using SPSSPDF unavailable
52Lecture 52: Principal Component Analysis (PCA): Conceptual ModelPDF unavailable
53Lecture 53: Principal Component Analysis (PCA): Extraction of Principal components (PCs)PDF unavailable
54Lecture 54: Principal Component Analysis (PCA): Model Adequacy and InterpretationPDF unavailable
55Lecture 55: Principal Component Analysis (PCA): Model Adequacy and Interpretation (contd) "PDF unavailable
56Lecture 56: Factor Analysis: Basics and Orthogonal factor modelsPDF unavailable
57Lecture 57: Factor Analysis: Types of models and key questionsPDF unavailable
58Lecture 58: Factor Analysis: Parameter EstimationPDF unavailable
59Lecture 59: Factor Analysis: Parameter Estimation(contd)PDF unavailable
60Lecture 60: Factor Analysis: Model Adequacy tests and factor rotationPDF unavailable
61Lecture 61: Factor Analysis: Factor scores and case studyPDF unavailable


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2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available