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
- Completion of Statistics 421 is highly recommended as preparation for this course.
Prerequisite(s)
- Statistics 323 or Mathematics 323; and Mathematics 267 or 277 or 353 or 381; or consent of the Department.
SyllabusSections
This course will be offered next in
Winter 2018.