MTH2133 Computational Bayesian Statistics
Bayesian statistics provide a powerful toolkit for modeling random processes and making predictions. The ideas behind these tools are simple, but expressing them mathematically can make them hard to learn and apply. This class takes a computational approach, which allows students with programming experience to use that knowledge as leverage. Students will work through a series of exercises in the book, Think Bayes, and help develop new material.
Concurrent Requisites
ENGR3533
Hours