Appl’d Multivar. Data Analysis

Catalog description

This course introduces different multivariate data analysis and modeling tools, which can be used for simultaneously analyzing data with multiple variables. It is designed to emphasize applied methodologies in different fields with a focus in the engineering field. Topics to be covered include: multivariate regression, logistic regression, multivariate analysis of variance (MANOVA), principal components analysis, cluster analysis, canonical correlation, factor analysis, and discriminant analysis. The effective use of data analysis software, such as SAS, for solving real-world engineering problems will also be addressed. Prerequisite: SSIE 505 or its equivalent. Terms offered varies.