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Abstract:
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The University of South Carolina statistics department recently modernized its undergraduate multivariate statistics course. Some traditional topics such as multivariate analysis of variance, multivariate regression, and canonical correlation analysis were deemphasized, in favor of more "modern" topics such as multiple logistic regression, classification and regression trees, and support vector machines. The goal is to teach more computational topics in order to meet the growing need for data mining and data science skills. We will discuss how the modernized course suits the needs of the course's varied audience, which includes undergraduate statistics majors, graduate students from other departments, and statistics students in the master's and applied master's programs.
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