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Bayesian Inference ○𓆪｜Definition｜1st｜20251119205401-00-⌔
Bayesian inference - Wikipedia
Bayesian inference
Bayesian inference (/ˈbeɪziən/BAY-zee-ən or/ˈbeɪʒən/BAY-zhən)1 is a method of statistical inference in which Bayes’ theorem is used to calculate a probability of a hypothesis, given prior evidence, and update it as more information becomes available. Fundamentally, Bayesian inference uses a prior distribution to estimate posterior probabilities. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, psychology2, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called “Bayesian probability”.
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