MAT 4381 Bayesian Inference
3 units
Mathematics
Faculty of Science
An introduction to the theory and practice of modern Bayesian inference. Choice of prior distributions and calculation of the posterior distribution for single and multi-parameter models. Computational approaches to Bayesian inference such as Markov Chain Monte Carlo and Gibbs sampling. Hierarchical and regression modelling in a Bayesian framework. Use of statistical software.
Components:
Lecture
Previously Offered Terms:
Winter
French Equivalent:
Organized
7 responses
4.14
/ 5
Clear Expectations
7 responses
3.57
/ 5
Learned a Lot
7 responses
4.71
/ 5
Fair Assessments
7 responses