Subject: STA 232C
Title: Applied Statistics III
School: College of Letters and Science LS
Department: Statistics STA
Effective Term: 2011 Fall
- Lecture - 3.0 hours
- Laboratory - 1.0 hours
Multivariate analysis: multivariate distributions, multivariate linear models, data analytic methods including principal component, factor, discriminant, canonical correlation and cluster analysis.
STA 106; STA 108; STA 131C; STA 232B; MAT 167
Expanded Course Description
Summary of Course Content:
Basic applied multivariate analysis, including Wishart distribution, Hotelling's t^2, MANOVA, principle components, factor analysis, canonical correlation, classification and cluster analysis.
Optional: Multidimensional scaling, elements of directional data, robustness, structured covariance matrices.
1. R. Gnanadesikan (1997), Methods for Statistical Data Analysis of Multivariate Observations, 2nd ed., Wiley
2. K.V. Mardia, J.T. Kent and J.M. Bibby (2000), Multivariate Analysis, Academic Press
Potential Course Overlap: