STA437H1: Methods for Multivariate Data


Practical techniques for the analysis of multivariate data; fundamental methods of data reduction with an introduction to underlying distribution theory; basic estimation and hypothesis testing for multivariate means and variances; regression coefficients; principal components and partial, multiple and canonical correlations; multivariate analysis of variance; profile analysis and curve fitting for repeated measurements; classification and the linear discriminant function.


STA302H1/​ STA352Y1 ( MAT224H1/​ MAT247H1 recommended )

Recommended Preparation: 
Distribution Requirements: 
Breadth Requirements: 
The Physical and Mathematical Universes (5)