Prior probabilities refer to the initial assessments of the likelihood of an event occurring before any new evidence is considered. These probabilities serve as a foundational component in probabilistic reasoning and are crucial in Bayesian networks, where they provide a baseline for updating beliefs in light of new data. By establishing these starting probabilities, one can apply Bayes' theorem to adjust the probability as new information becomes available, leading to more informed decision-making.
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