 Posterior predictive distribution

The posterior predictive distribution is a concept in Bayesian statistics used to make predictions about future observations based on a model that has been updated with observed data. It combines information about the uncertainty of the model parameters (as described by the posterior distribution) with the likelihood of new data given those parameters. Here’s a breakdown of the concept: 1. **Posterior Distribution**: After observing data, we update our beliefs about the model parameters using Bayes' theorem.