Subject: STA 232B
Title: Applied Statistics
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
Alternative approaches to regression, model selection, nonparametric methods amenable to linear model framework and their applications.
Prerequisites
STA 106; STA 108; STA 131A; STA 131B; STA 131C; STA 232A; MAT 167
Expanded Course Description
Summary of Course Content:
Alternative approaches to regression such as ridge and partial least squares, model selection, mixed ANOVA models, and other penalty approaches.
Nonparametric function estimation methods amenable to a linear model framework (such as spline, polynomial, wavelet etc.).
Optional: Basic ideas of extrapolation and interpolation, basics of survey sampling, and choice of good bases.
Illustrative Reading:
Possible textbooks:
1. J. Jiang (2007): Linear and generalized linear mixed models and their applications, Springer
2. W.N. Venables and B.D. Ripley (2003): Modern applied statistics with S-plus, 4th ed, Springer
3. S.R. Jammalamadaka & D. Sengupta (2003) Linear Models: An Integrated Approach, World Scientific
4. J.S. Simonoff (1996) Smoothing Methods in Statistics, Springer
5. J. Faraway (2005) Linear Models with R, Chapman & Hall/CDC
Potential Course Overlap:
None