530—Applied Multivariate Statistics and Data Mining (3) (Prereq: STAT 515 or PSYC 228 or MGSC 391 or equivalent) Introduction to fundamental ideas in multivariate statistics using case studies. Descriptive, exploratory, and graphical techniques; introduction to cluster analysis, principal components, factor analysis, discriminant analysis, Hotelling's T2and other methods.
Usually Offered: Fall Even Years
Purpose: To introduce students with a variety of statistical backgrounds to the basic ideas in multivariate statistics. It will cover the assumptions, limitations, and uses of basic techniques such as cluster analysis, principal components analysis, and factor analysis as well as how to implement these methods in R, SAS, and/or SPSS. Instead of theoretical development, the focus will be on the intuitive understanding and applications of these methods to real data sets by the students.
Current Textbook: An R and S-PLUS Companion to Multivariate Analysis by Brian Everitt, Springer, 2005.
|Introduction to Multivariate Data,
R, SAS, and SPSS
|Multivariate Graphical Displays||
|MANOVA and Discriminant Analysis||
|Canonical Correlation Analysis||
|Survey of Other Methods||
The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.