Bayesian statistical modeling and data analysis

Spring 2025

Schedule

Week	Date	Topic	Reading	Notes	Assignment
1	Wed Jan 08	lab: welcome		💻	hello R
	Fri Jan 10	intro, history, notation	Ch. 2		hw 0
2	Mon Jan 13	lab: MLE		💻
	Wed Jan 15	probability, exchangeability	Ch. 2	🗒 📝	hw 1
	Fri Jan 17	beta-binomial model	Ch. 3	🗒 📝
3	Mon Jan 20	NO CLASS
	Wed Jan 22	Poisson-gamma model, exp families	Ch. 3	🗒 📝	hw 2
	Fri Jan 24	reliability (conf. intervals, hpd, Laplace approx.)	Ch. 3	🗒 📝
4	Mon Jan 27	lab: exp. families and transformations		💻
	Wed Jan 29	intro to Monte Carlo	📖	🗒 📝	hw 3
	Fri Jan 31	predictive checks and MC error	Ch. 4	🗒 📝
5	Mon Feb 03	lab: mixture densities		💻
	Wed Feb 05	the normal model	Ch. 5	🗒📝	hw 4
	Fri Feb 07	estimators	Ch. 5	🗒📝
6	Mon Feb 10	lab: normal data & estimators		💻
	Wed Feb 12	priors		🗒📝
	Fri Feb 14	review
7	Mon Feb 17	Jeffreys prior; exam review		💻
	Wed Feb 19	Exam I
	Fri Feb 21	Metropolis algorithm	Ch. 10	🗒
8	Mon Feb 24	lab: Metropolis algo.		💻
	Wed Feb 26	MCMC diagnostics	Ch. 6, 10	🗒📝	hw 5
	Fri Feb 28	Gibbs sampling	Ch. 6	🗒
9	Mon Mar 03	lab: MCMC and conf. bands		💻
	Wed Mar 05	multivariate normal	Ch. 6	🗒	hw 6
	Fri Mar 07	Bayesian regression	Ch. 7, background	🗒📝
10	Mon Mar 10	NO CLASS
	Wed Mar 12	NO CLASS
	Fri Mar 14	NO CLASS
11	Mon Mar 17	lab: rstanarm		💻
	Wed Mar 19	hierarchical modeling	Ch. 8	🗒📝	hw 7
	Fri Mar 21	model averaging	Ch. 9 sec. 3	🗒
12	Mon Mar 24	lab: probit regression		💻
	Wed Mar 26	mixed effects models	Ch. 11	📝.R
	Fri Mar 28	review
13	Mon Mar 31	lab: exam review
	Wed Apr 02	Exam II
	Fri Apr 04	Hamiltonian Monte Carlo	📖	🗒
14	Mon Apr 07	lab: inverse problem		💻	hw 8
	Wed Apr 09	Bayesian inverse problems	📖	🗒
	Fri Apr 11	missing data	Ch. 7	📝.R
15	Mon Apr 14	lab: office hours / final review
	Wed Apr 16	practice for final