Monday 11 November – Wednesday 13 November 2019 (Dr Matthew Schofield)


Bayesian methods are increasingly popular in many scientific disciplines. This workshop will cover the foundations of Bayesian methods with a focus on application. A variety of examples will be used to show how to fit Bayesian models using freely available statistical software packages R, JAGS and Stan. We will consider standard models (e.g. linear regression) as well as complex (e.g. hierarchical models and missing data). There will be opportunity for hands-on application with participants fitting models to data.

This course will also cover the statistical theory needed to understand the methods. This will include discussion and demonstration of the simulation approaches (Markov chain Monte Carlo) that enable the fitting of Bayesian models.

The workshop is aimed at quantitative researchers who would like to learn more about using Bayesian approaches in their research. Participants should have a good foundation in basic statistical modeling and inference, e.g. an understanding of estimation in linear regression. Basic knowledge of R will also be assumed.


Please register by Friday 1 November 2019