STAT 451
Applied Bayesian Statistics
Statistics
College of Physical and Mathematical Sciences
Course Description
Bayesian analogs of t-tests, regression, ANOVA, ANCOVA, logistic regression, and Poisson regression implemented using Nimble, Stan, JAGS and Proc MCMC.
When Taught
Winter
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Min
3
Fixed
3
Fixed
3
Fixed
0
Title
Write code in R
Learning Outcome
Students will be able to generate their own analysis of Bayesian models in R.
Title
Understand, Explain, and Demonstrate
Learning Outcome
Students will be able to understand, explain and demonstrate basic Bayesian theory and its usefulness in real-world applications.
Title
Fit and Interpret Bayesian Model
Learning Outcome
Students will be able to apply, implement and interpret a fully Bayesian approach to relevant statistical problems, including design, model selection, model fit steps.
