5. More on PDFs

In this chapter we collect material addressing various aspects of probability distributions (PDFs).

• The posteriors we will encounter will in general be multi-dimensional. We first consider some aspects of one-dimensional (1D) posteriors in One-dimensional PDFs and two-dimensional (2D) posteriors in Two-dimensional PDFs. There is a follow-up exercise notebook for exploring 1D and 2D PDFs using Python libraries with the other part I exercises (📥 Exercise: Exploring PDFs).

• Bayesian credible intervals provides further details on defining Bayesian credible intervals and on the relationship to frequentist confidence intervals.

• In The Central Limit Theorem we take a first look at the central limit theorem (CLT), including a proof and several visualizations.