Instructor: Merlise Clyde
| Office: | |
| Phone: | 681-8440 |
| Email: | clyde@stat.duke.edu |
| Office Hours: | Monday 2:30-3:30, or by appointment |
Teaching Assistant: Zhenglei Gao
| Office: | |
| Phone: | 684-4365 |
| Email: | zhenglei@stat.duke.edu |
| Office Hours: | TBA |
Meeting Times: Tuesday-Thursday 2:15 - 3:30 025 Old Chemistry Building
This courses covers concepts of linear models from Bayesian and classical viewpoints using a vector space approach. Topics include: simple linear and multiple regression, parameter estimation and interpretation, distribution theory for ANOVA and testing, variable transformations and selection, prediction, model diagnostics, Bayesian hierarchical models, Bayes factors and model selection, and Bayesian model averaging. Extensions to Multivariate models and nonparametric mmodels if time permits. Prerequisite: Statistics 213 or equivalent. Knowledge of linear algebra is extremely useful.
Grading will be based on Homeworks, Midterms (In-class/Takehome) and Final.
The following books will be useful for the course:
The first three will be at the book store or are available directly from Springer, Amazon or other sites. (Search for the best price)