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Prerequisite: MATH 307. Offered every 3 semesters.
Techniques of multivariate statistical analysis are illustrated by examples from various fields. Course includes an applied project ( a thorough analysis of real-life data sets using computer-packaged programs). Topics include: multivariate normal distribution; sample geometry and multivariate distances; inference about a mean vector; comparison of several multivariate means, variance and covariances; detection of multivariate outliers; principle components; factor analysis; canonical correlation; discriminant analysis; and multivariate multiple regression.
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