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where P(H<sub>0</sub>) is the prior probability that the hypothesis is true; P(D|H<sub>0</sub>) is the [[conditional probability]] of the data given that the hypothesis is true, but given that the data are known it is the [[likelihood function|likelihood]] of the hypothesis (or its parameters) given the data; P(H<sub>0</sub>|D) is the posterior probability that the hypothesis is true given the data. P(D) should be the probability of producing the data, but on its own is difficult to calculate, so an alternative way to describe this relationship is as one of proportionality:
:<math>P(H_0|D) \
Since P(H|D) is a probability, the sum over all possible (mutually exclusive) hypotheses should be 1, leading to the conclusion that
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