Posterior probabilities represent the updated likelihood of a hypothesis being true after considering new evidence or data. This concept is central to Bayesian inference, where prior beliefs about a hypothesis are combined with observed data to produce revised probabilities. Essentially, posterior probabilities help us quantify our uncertainty and make informed decisions based on both prior knowledge and new information.
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