MAT 367
Multivariate Analysis · 3 credits · Spring 2027
Requirements
Prerequisite: ENG 201 and MAT 302 and MAT 310
About this course
Multivariate statistical analysis refers to techniques for examining relationships among multiple variables at the same time. In this course students will study a variety of standard statistical methods used to analyze multivariate data, emphasizing the implementation and interpretations of these methods. Topics covered include matrix computation of summary statistics, graphical techniques, the multivariate normal distribution, MANOVA, principal component analysis, factor analysis, and other topics such as canonical correlation and cluster analysis. Students will use the R statistical computing package for data analysis.
No sections have been posted for this course in this term yet.