Subject: STA 232C
Title: Applied Statistics III
Units: 4.0
School: College of Letters and Science LS
Department: Statistics STA
Effective Term: 2011 Fall
Learning Activities
- Lecture - 3.0 hours
- Laboratory - 1.0 hours
Description
Multivariate analysis: multivariate distributions, multivariate linear models, data analytic methods including principal component, factor, discriminant, canonical correlation and cluster analysis.
Prerequisites
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.
Illustrative Reading:
Possible textbooks:
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:
None