4 credits Explores probability distribution of random vectors, covariance matrix, multivariate normal distributions, inferences about a mean vector and several multivariate mean vectors, principal component analysis, and discriminant analysis. Graded (A-F) only. Must be eligible to take Graduate level coursework. Prerequisite(s): MTH 361 is required. MTH 261 is strongly recommended.
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