The posterior distribution is the updated probability distribution that reflects new evidence or data, calculated using Bayes' theorem. It combines prior beliefs about a parameter with the likelihood of observed data, resulting in a more informed estimate of that parameter. This concept is crucial in Bayesian statistics, where it allows for the incorporation of prior knowledge and uncertainty into statistical inference.
congrats on reading the definition of Posterior Distribution. now let's actually learn it.