Introduction to Bayesian statistics using BUGS
Monday 30 March 2020 – Tuesday 31 March 2020 – UNFORTUNATELY THIS COURSE HAS BEEN CANCELLED
NEXT COURSE DATE: 20th and 21st October
Venue: Seminar rooms, Institute of Public Health, Forvie Site, Robinson Way, Cambridge, CB2 0SR [note access is via Robinson Way not Knightly Avenue/Musgrave Drive] (University map, Google map, directions)
- Day 1 – Introduction to the use of Monte Carlo methods, Bayesian methods, Markov chain Monte Carlo (MCMC), regression models, and implementation in OpenBUGS/WinBUGS or JAGS/OpenBUGS/WinBUGS via R.
- Day 2 – Generalised linear models, predictions, missing data, model criticism, model comparison and assessing sensitivity to prior distributions, introduction to hierarchical models.
See course details for the full timetable.
The emphasis throughout will be on practical examples: software and code to carry out all the analyses will be provided (see software download). Participants are encouraged to bring their own laptops for the practicals.
The target audience of the course is statisticians and applied researchers in any subject area. No experience of Bayesian methods or specialist software will be assumed but do we assume familiarity with key statistical concepts, specifically:
- Basic probability concepts: discrete and continuous random variables; probability density functions; expectation; variance; familiarity with standard probability distributions (e.g. normal, binomial, uniform).
- A good understanding of classical (ie non-Bayesian) statistical modelling: likelihood (as in maximium likelihood estimation) and sampling distributions; linear regression; generalised linear models including logistic regression; assessment of model fit using residuals.
We also run a companion course Advanced Bayesian Modelling with BUGS.