Here are links to my M249 tutorial delivered on 27 Mar 2021: * Bayesian Methods*. This tutorial introduced Bayes' Theorem and its components, along with inferences and hypothesis testing:

- Probability & Bayes’ Theorem
- Prior probabilities
- Likelihoods & conjugate analysis
- Estimates & inferences
- Hypothesis testing (additional topic, not part of M249)

This tutorial is for the 20J presentation (Sep 2020) and materials will expire after 12 months - except for OU Library resources.

**SLIDES**

http://www.open.ac.uk/documents/2/ka21110326275243.pdf

Please do let me know if you spot any errors or ambiguities!

**TUTORIAL RECORDING**

**OU LIBRARY DOWNLOADABLE FULL TEXT E-BOOKS**

*A Modern Introduction To Probability And Statistics : Understanding Why And How*by Dekking, Michel*Fundamentals of Data Analytics: With a View to Machine Learning*by Mathar, R. et al. (2020)*Data Analysis: A Bayesian Tutorial*by Sivia & Skilling (2006)

I highly recommended the Sivia & Skilling book - it's very readable, has a very approachable style and lots of examples of using Bayesian methods.