DATA 331 Introduction to Multivariate Analytics

Applied approach to multivariate analysis for data science. Topics may include multivariate normal distribution, supervised and unsupervised dimensionality reduction, principal component analysis, partial least-squares, discriminant analysis, and cluster analysis. Use of an open-source data science platform, such as R. 

Credits

4

Prerequisite

DATA 202 and MATH 228, or permission of department chair.

General Education

Offered

  • Fall