Applied Multivariate Analysis

By Sugata Sen Roy | University of Calcutta

Learners enrolled: 1351

The Applied Multivariate course caters to two objectives. On one hand it extends the usual univariate statistical methods to several dependent variables. On the other, it develops techniques which are peculiar to several variable studies only. In the former the discussions are on multivariate distributions, multivariate testing, multivariate linear models, including multivariate regression and multivariate ANOVA. The latter introduces grouping techniques like Cluster Analysis and Classification problems, dimension reduction methods like principal Component Analysis and Factor Analysis, and several such topics. The course is a mix of basic theory and their applications and is likely to be useful for both postgraduate students of Statistics and also students of other disciplines who uses statistical methods for their analyses.

Summary

Course Status :	Completed
Course Type :	Core
Duration :	15 weeks
Category :	Mathematics
Credit Points :	3
Level :	Postgraduate
Start Date :	13 Jul 2020
End Date :	25 Oct 2020
Enrollment Ends :	31 Aug 2020
Exam Date :	15 Nov 2020 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week Module

1 1 Introduction to Multivariate Analysis

2 Multivariate Distributions

3 Multivariate Normal Distribution and Related Results 1

2 4 Multivariate Normal Distribution and Related Results 2

5 Multivariate Normal Distribution and Related Results 3

6 Multivariate Normal Distribution and Related Results 4

3 7 Classification of Individuals

8 Cluster Analysis 1

9 Cluster Analysis 2

4 10 Cluster Analysis 3

11 Cluster Analysis 4

12 Cluster Analysis 5

5 13 Discriminant Analysis and Classification 1

14 Discriminant Analysis and Classification 2

15 Discriminant Analysis and Classification 3

6 16 Discriminant Analysis and Classification 4

17 Principal Components Analysis 1

18 Principal Components Analysis 2

7 MID TERM ASSESSMENT

8 19 Principal Components Analysis 3

20 Principal Components Analysis 4

21 Principal Components Analysis 5

9 22 Factor Analysis 1

23 Factor Analysis 2

24 Factor Analysis 3

10 25 Factor Analysis 4

26 Factor Analysis 5

27 Canonical Correlations 1

11 28 Canonical Correlations 2

29 Multidimensional Scaling

30 Correspondance Analysis

12 31 Multivariate Linear Models 1

32 Multivariate Linear Models 2

33 Multivariate Linear Models 3

13 FINAL ASSESSMENT

Instructor bio

Sugata Sen Roy

University of Calcutta

I had been teaching at the postgraduate level for the last 30 years. My research and teaching interests have been regression analysis, time series analysis, econometrics, development statistics, multivariate analysis and survival analysis. I have had several publications in these areas and have also guided Ph.D. students in related areas. However, my primary focus has been on teaching statistics and particularly in dissipating statistical knowledge to students of other disciplines.