Probability and an introduction to Bayes’ theorem

Understanding the basics of probability and applying Bayesian inference to data

Welcome to the second workshop of the BayesCog course!

In this workshop, we’ll explore the fundamental concepts of probability and introduce Bayes’ theorem, which forms the foundation of Bayesian statistics. We’ll start with basic probability concepts and gradually build up to understanding how a Bayesian approach to probability involves updating our knowledge based on evidence.

By the end of this workshop, you will be able to:

• Distinguish discrete and continuous probability and work with common distributions in R
• Compute joint, marginal and conditional probabilities
• State Bayes’ theorem and identify the prior, likelihood, posterior and marginal likelihood
• Use Bayes’ theorem to solve basic statistical problems

Working directory for this workshop

Model code and R scripts for this workshop are located in the (/workshops/01.R_basics) directory. Remember to use the R.proj file within each folder to avoid manually setting directories!