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
	Wed Apr 09	Bayesian inverse problems
	Fri Apr 11	Special topic
15	Mon Apr 14
	Wed Apr 16	practice for final