Syllabus

This is an approximate schedule. I will update it as needed during the semester.

08/27 - 08/31	Review of probability and Bayes' theorem
	Lab Fri. 8/31
	Reading: Berry Chapters 4 and 5
09/05 - 09/10	Bayesian inference for proportions
	09/03 Labor Day; no class
	Reading: GCSR, Section 2.1 - 2.5
09/12 - 09/14	Summarizing posterior distributions
	Lab Fri. 09/14
09/17 - 09/21	Other 1-parameter models
	Reading: GCSR Section 2.6-2.9
09/24 - 09/28	Intro to multiparameter models
	Lab Fri. 09/28
	Reading: GCSR Ch 3

10/01 - 10/05	Bayesian computing
	Midterm 1
	Reading: GCSR Ch 10 and GCSR Sections 11.1-11.6, 11.10
10/08 - 10/12	Hierarchical models
	Lab Fri. 10/12
	Reading: GCSR, Ch. 5
	selections from WinBUGS manual
10/15 - 10/19	Hierarchical models; More Bayesian computing
10/22 - 10/26	Bayesian Regression
	Reading: GCSR Ch 14
	Lab Fri. 10/26
10/29 - 11/02	Hierarchical regression models
	Midterm 2
11/05 - 11/09	Hierarchical, continued; model checking and comparison
	Project proposals due Mon. 11/05
	Lab. Fri. 11/09
	Reading: GCSR Ch. 6
11/12 - 11/16	Hypothesis testing, etc. continued
11/19 - 11/23	No class
11/26 - 11/30	Special topics
	Project interim reports due Wed. 11/28
	Lab. Fri. 11/30
	Reading: Lee Ch 7
12/03 - 12/07	Special topics; empirical Bayes methods
	Reading: Carlin and Louis, Ch. 3
12/10 - 12/14	Project presentations and review
	Projects due 12/10
	Lab Fri. 12/14
12/21	Final exam, 7:30 a.m.