ISL 509 - MULTIVARIATE STATISTICAL ANALYSIS

Course Objectives

To understand the main features of multivariate data.
To be able to use exploratory and confirmatory multivariate statistical methods properly.
To be able to carry out multivariate statistical techniques and methods efficiently and effectively.

Course Description

Aspects of multivariate analysis, random vectors, sample geometry and random sampling, multivariate normal distribution, inferences about the mean vector, MANOVA. Analysis of covariance structures: principal components, factor analysis. Classification and grouping techniques: discrimination and classification, clustering, logistic regression model, use of statistical computer packages.