Prior probability is the initial estimation of the likelihood of an event or hypothesis before considering new evidence. It forms the backbone of Bayesian inference, serving as the starting point for updating beliefs based on observed data. Understanding prior probability is crucial as it influences the posterior probability, which combines prior beliefs with new evidence to refine predictions or conclusions.
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