Bayesian inference is the re-allocation of credibilities over possibilities [Krutschke 2015]. This means that a bayesian statistician has an “a priori” opinion regarding the probabilities of an event: p(d) (1) By observing new data x, the statistician will adjust his opinions to get the "a posteriori" probabilities. p(d|x) (2) The conditional probability of an event d given x is the share of …
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