STAT 4130

Applied Multivariate Statistics

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Course Description

Prerequisites

A prior course in mathematical statistics, a prior course in linear algebra, and a prior course in programming

This course develops fundamental methodology to the analysis of multivariate data using computational tools. Topics include multivariate normal distribution, multivariate linear model, principal components and factor analysis, discriminant analysis, clustering, and classification.

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