This table gives a tentative timetable for the course. Everything in it, including the dates of homeworks and exams, is subject to change.
Tuesday  Þursday  

Tuesday  Þursday  
Wk01 
Jan 24
Part One: Bayesian Parameter Estimation Bayesian Probability 
Jan 26
Part One: Bayesian Parameter Estimation Posterior Probability Distributions 
Wk02 
Jan 31
Part One: Bayesian Parameter Estimation Bayesian Point & Interval Estimation; Gaussian Approximation; Problem Set 1 due 
Feb 2
Part One: Bayesian Parameter Estimation Reparametrization; Noninformative and Improper Priors; Inference about future observations 
Wk03 
Feb 7
Part One: Bayesian Parameter Estimation Sampling from a posterior; Problem Set 2 due 
Feb 9
Part One: Bayesian Parameter Estimation Multiparameter posteriors; Gaussian approximation and Hessian Matrix 
Wk04 
Feb 14
Part One: Bayesian Parameter Estimation Marginalization; Problem Set 3 due 
Feb 16
Part One: Bayesian Parameter Estimation Multinomial Distribution 
Wk05 
Feb 21
Part Two: Bayesian Model Selection Bayes factor and Jaynesian Evidence; Problem Set 4 due 
Feb 22
Review for Prelim Exam 1 
Wk06 
Feb 28
FIRST PRELIM EXAM 
Mar 1
Part Two: Bayesian Model Selection Posterior predictive checking 
Wk07 
Mar 7
Part Two: Bayesian Model Selection Poisson Process Example 
Mar 9
Part Two: Bayesian Model Selection Linear Regression Example; Problem Set 5 due 
Mar 14
No Class (Spring Break) 
Mar 16
No Class (Spring Break) 

Wk08 
Mar 21
Part Three: Computational Methods Importance sampling; MarkovChain Monte Carlo (Metropolis Algorithm) 
Mar 23
Part Three: Computational Methods MCMC Demonstration and Example; Problem Set 6 due 
Wk09 
Mar 28
Part Three: Computational Methods Gibbs Sampler 
Mar 30
Part Three: Computational Methods JAGS; Problem Set 7 due 
Wk10 
Apr 4
Part Three: Computational Methods Maximum Entropy 
Apr 6
Part Three: Computational Methods Hamiltonian Monte Carlo; Problem Set 8 due 
Wk11 
Apr 11
Part Three: Computational Methods STAN 
Apr 13
Review for Prelim Exam 2; Problem Set 8½ due 
Wk12 
Apr 18
Project brainstorming session 
Apr 20
SECOND PRELIM EXAM 
Wk13 
Apr 25
Part Four: Generalized Linear Models Multivariate linear models 
Apr 27
Part Four: Generalized Linear Models Multivariate linear models Problem Set 9 due 
Wk14 
May 2
Part Four: Generalized Linear Models Logistic Regression

May 4
Part Four: Generalized Linear Models Logistic Regression Example Problem Set 10 due 
Wk15 
May 9
Project presentations 
May 11
Project presentations; Problem Set 11 due 
Last Modified: 2018 April 11
Dr. John T. Whelan / john.whelan@astro.rit.edu / Professor, School of Mathematical Sciences & Center for Computational Relativity and Gravitation, Rochester Institute of TechnologyThe contents of this communication are the sole responsibility of Prof. John T. Whelan and do not necessarily represent the opinions or policies of RIT, SMS, or CCRG.