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BST 558 Applied Multivariate Analysis 3.0 Credits

This course introduces students to statistical methods for describing and analyzing multivariate data. Topics to be covered include basic matrix algebra, multivariate normal distribution; linear models with multivariate response, multivariate analysis of variance; profile analysis, dimension reduction techniques, including principle component analysis, factor analysis, canonical correlation, multidimensional scaling; discriminate/cluster analysis; and classification/regression trees.

College/Department: Dornsife School of Public Health
Repeat Status: Not repeatable for credit
Prerequisites: BST 551 [Min Grade: C]

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