The probability assigned to a hypothesis or event before a piece of evidence emerges. In Bayesian reasoning, the probability after a piece of evidence (the posterior probability) is a function of the prior probability, and the extent to which the evidence fits the hypothesis, but inversely proportional to the prior probability of the evidence—in other words, evidence that might be expected to have arisen on many different hypotheses does not confirm any one of them particularly well. The terminology is criticized by de Finetti, who prefers to talk of initial and final probabilities.