In Bayesian statistics, the posterior probability of a random event or an uncertain proposition is the conditional probability that is assigned after the relevant evidence is taken into account. Similarly, the posterior probability distribution is the distribution of an unknown quantity, treated as a random variable, conditional on the evidence obtained from an experiment or survey.
Read more about Posterior Probability: Definition, Example, Calculation, Classification
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“Only in Britain could it be thought a defect to be too clever by half. The probability is that too many people are too stupid by three-quarters.”
—John Major (b. 1943)
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