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Syllabus

This is an approximate schedule. I will update it as needed during the semester. Unless identified otherwise, readings are in the textbook by Bolstad. ``GCSR," ``Lee," and ``C and L" refer to the books by Gelman, Carlin, Stern, and Rubin; by Lee; and by Carlin and Louis, all of which are on reserve in the Mathematical Sciences Library.

08/21 - 08/25 Review of probability and Bayes' theorem
  Lab Fri. 8/25
  Reading: Chapters 1 and 4
08/28 - 09/01 Bayesian inference for proportions
  Reading: Chapters 5, 6, and 8
09/06 - 09/08 Summarizing posterior distributions
09/04 Labor Day; no class
  Reading: Chapter 9
  Lab Fri. 09/08
09/11 - 09/15 Other 1-parameter models
  Reading: Ch 7 and 10
09/18 - 09/22 Intro to multiparameter models
  Lab Fri. 09/22
  Reading: (*GCSR Ch 3)
09/25 - 09/29 Bayesian computing
  Midterm 1
  Reading: (*GCSR Ch 10 and GCSR Sections 11.1-11.6, 11.10)
10/02 - 10/06 Hierarchical models
  Lab Fri. 10/06
  Reading: (*GCSR, Ch. 5),
  selections from WinBUGS manual
10/09 - 10/13 Hierarchical models; More Bayesian computing

10/16 - 10/20 Bayesian Regression
  Reading: (Ch 13, and *Lee sections 6.3-6.4)
  Lab Fri. 10/20
10/23 - 10/27 Hierarchical regression models
  Midterm 2
10/30 - 11/03 Hierarchical, continued; model checking and comparison
  Project proposals due Mon. 10/30
  Lab. Fri. 11/03
  Reading: (*GCSR Ch. 6)
11/06 - 11/10 Hypothesis testing, etc. continued
11/13 - 11/17 Special topics
  Project interim reports due Fri. 11/17
  Lab. Fri. 11/17
  Reading: (Ch 14, *Lee Ch 7)
11/20 - 11/24 No class
11/27 - 12/01 Special topics; empirical Bayes methods
  Reading: (*C and L, Ch. 3)
12/04 - 12/08 Project presentations and review
  Projects due 12/04
  Lab Fri. 12/08
12/12 Final exam, noon


next up previous
Next: About this document ... Up: syllabus2006 Previous: College administering this course
Kate Cowles 2006-08-07