Bayesian Statistics for Applied Research

This two-day course provides a practical and accessible introduction to Bayesian statistics for applied research in any field. Students will benefit from a combination of lectures and discussion to explore fundamental concepts unlocking the potential to design bespoke statistical analyses based on your data and hypotheses as well as practical exercises to gain hands-on experience implementing Bayesian models using free and open-source software. The course is designed as a springboard to overcome the steepest part of the Bayesian learning curve with an immersive two-day deep-dive.

Students will have the opportunity to schedule a follow-up Bayesian surgery appointment (30 mins in-person or remote) for one-to-one engagement (or small groups, as preferred) with the course instructor to answer burning questions that remain and/or to troubleshoot technical challenges related to their own research applications.

Pre-requisites: Students will need good programming skills in R and a basic understanding of linear regression to be successful in this course.

Places will be allocated on a first-come, first-served basis, and once places are full, we will maintain a waiting list.

Please only register if you are certain of your availability and commitment to attend.

This event is not delivered by the SWDTP. For enquiries, please contact granduniondtp@socsci.ox.ac.uk