Fundamentals of Bayesian inference, single and multiparameter models, hierarchical models, regression models, generalized linear models, advanced computational methods, Markov chain Monte Carlo.
This course may not be repeated for credit.
Notes
- Statistics 421 is highly recommended as preparation.
Prerequisite(s)
- Statistics 323 or Mathematics 323 and Mathematics 353 or 381; or consent of the Division.
SyllabusSections
This course will be offered next in
Winter 2016.