Computational Methods for Bayesian Statistics

About this programme

No fees are charged for EU and EEA citizens, Swedish residence permit holders and exchange students. The course gives an introduction to Bayesian statistical modelling and inference, focusing on computational methods such as Markov chain Monte Carlo (MCMC) and other simulation methods, but also looking at tools such the EM algorithm. We emphasize the interplay between statistical modelling and applied problem solving, as well as computational and theoretical aspects of the models. The course requires a strong background in mathematics, at least one course in statistics, and skills in scientific programming (for example in R or Python) as achieved by completing MSG400 "Stochastic Data Processing and Simulation". All eligible applicants who have applied before the deadline will be granted a place. Mathematical Sciences is a joint department of Chalmers/University of Gothenburg. Your education takes place in the spacious and bright premises of Mathematical Sciences at the Chalmers campus Johanneberg, where there are lecture halls, computer rooms and group rooms. Here you can also find student lunch room and reading room, as well as student counsellors and student office.