STAT 5610 - Applied Multivariate Statistical Methods

An applied treatment of multivariate procedures is presented. Classical procedures such as Hotelling’s T-squared methods are discussed for the one and two sample problems and MANOVA for standard designs. Topics that will be accentuated are principal components, discriminant analysis, cluster analysis, and factor analysis. Emphasis will be on graphical methods and applications.

Prerequisites/Corequisites: Prerequisites: An introductory statistics course such as STAT 2600 or STAT 3640 and a course in linear algebra.

Credits 3 hrs.

Notes:
Open to Upperclass and Graduate Students. Undergraduates with junior or senior standing and 12 or more credit hours of work in mathematics and statistics may enroll in 5000-level courses with prior approval of the department chairperson.