MATH 429 - Applied Multivariate Analysis

Techniques of multivariate statistical analysis illustrated by examples from various fields. Topics include: Multivariate normal distribution. Sample geometry and multivariate distances. Inference about a mean vector. Comparison of several multivariate means, variances, and covariances. Detection of multivariate outliers. Principle components. Factor analysis. Canonical correlation. Discriminant analysis. Multivariate multiple regression. Course includes an applied project (a thorough analysis of real-life data sets using computer-packaged programs).
Prerequisites
Prerequisites: MATH 427 or ECON 318.
When Offered
Offered every 3 semesters.
(3 cr.)

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