Posterior predictive checks are a Bayesian model evaluation technique used to assess how well a model fits the observed data by comparing the predicted outcomes generated from the posterior distribution to the actual data. This approach allows researchers to visualize and quantify discrepancies between observed and expected outcomes, helping to determine if the model is adequately capturing the underlying data-generating process.
congrats on reading the definition of Posterior Predictive Checks. now let's actually learn it.