The posterior distribution is a probability distribution that represents the updated belief about a parameter after observing new data, combining prior beliefs with the likelihood of the observed data. It is a key concept in Bayesian statistics, where the posterior is calculated using Bayes' theorem, which formalizes how to update beliefs in light of new evidence. This distribution provides insights into the uncertainty and variability of the estimated parameters.
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