2022-2023 Undergraduate/Graduate Catalog

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