Multivariate Analysis

COURSE SUMMARY

The aims of this course are

To illustrate extensions of univariate statistical methodology to multivariate data.
To introduce students to some of the distinctive statistical methodologies which arise only in multivariate data.
To introduce students to some of the computational techniques required for multivariate analysis available in standard statistical packages.

Topics include: multivariate techniques and analyses, multivariate analysis of variance, principal component analysis and factor analysis, canonical correlation analysis, cluster analysis, discrimination and classification.

The course uses the R software for statistical computing. Students are expected to be familiar with the usage of the software.

PREREQUISITES

Students are expected to have background on undergraduate probability, mathematical statistics, and linear regression. Computer programming knowledge on R and/or C/C++ is required.