This course equips learners with the theoretical knowledge and computational skills needed to implement modern Bayesian statistical methods in real-world settings. By completing the course, learners ...

This course covers the ideas underlying statistical modelling in science through the lens of causal thinking. We cover the implementation of these ideas through Bayesian computational methods and ...

A semester-long study of topics in Statistics. Topics and emphases will vary according to the instructor. This course may be repeated for credit with different topics. See the details in the schedule ...

Articulate the need for computational approaches, such as Markov chain Monte Carlo (MCMC) algorithms, to Bayesian inference. Implement various MCMC algorithms to find posterior distributions, ...