Posterior Distribution

A posterior distribution is a way to update our beliefs about a parameter after seeing new data. Starting with an initial belief (prior), we combine it with observed information using Bayes' theorem. The result—the posterior distribution—reflects our updated understanding, balancing what we initially thought with what the data suggests. It's like refining an estimate as more evidence becomes available, helping us make more informed decisions based on both prior knowledge and actual data.