Introduction to Bayesian Analysis

15 March 2021–16 March 2021, 9:30 am–1:00 pm

This course focuses on the principles of Bayesian analysis with the aim to enable participants to apply Bayesian methods on their own research and understand other people's results via Bayesian analysis.

NOTE: Due to the coronavirus outbreak, all courses will now be delivered online through a live video feed. You can expect the same level of group and individual support as you would have received in our face-to-face courses.

Bayesian analysis is an alternative approach to the statistical techniques that are commonly used throughout most of the research world for the analysis of data. It's core principle stems for the idea that experiments are not abstract devices, hence knowledge existent prior to an experiment should be incorporated formally and openly in the analysis.

This course is aimed at professionals who want to be able to understand the fundamental principles of the Bayesian analysis in order to assist their own research as well as interpret other people's findings. By the end of this workshop, delegates should be able to understand and critically evaluate published research that has used Bayesian analysis as well as be confident to implement Bayesian concepts in their own research.

It is desirable for the course participants to have basic knowledge of statistics, i.e. notion of statistical inference, p-values and Confidence intervals.