STAT225: Multivariate Statistical Methods

Introduction to statistical methods for analyzing data sets in which two or more variables play the role of outcome or response. Descriptive methods for multivariate data. Matrix algebra and random vectors. The multivariate normal distribution. Likelihood and Bayesian inferences about multivariate mean vectors. Analysis of covariance structure: principle components, factor analysis. Discriminant, classification and cluster analysis. Prerequisite(s): STAT 205 or STAT 205B or STAT 208. Enrollment is restricted to graduate students. Undergraduates may enroll by permission of the instructor if they've completed STAT 205 or STAT 205B or STAT 208 (subject to instructor verification).

5 credits

Year Fall Winter Spring Summer

Formerly AMS 0225

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