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text: '"Posterior [1rf probability]" or "posterior [1rb odds]" refers our state of belief *after* seeing a piece of new evidence and doing a [1ly Bayesian update]. Suppose there are two suspects in a murder, Colonel Mustard and Miss Scarlet. Before determining the victim's cause of death, perhaps you thought Mustard and Scarlet were equally likely to have committed the murder (50% and 50%). After determining that the victim was poisoned, you now think that Mustard and Scarlet are respectively 25% and 75% likely to have committed the murder. In this case, your "[1rm prior probability]" of Miss Scarlet committing the murder was 50%, and your "posterior probability" *after* seeing the evidence was 75%. The posterior probability of a hypothesis $H$ after seeing the evidence $e$ is often denoted using the [1rj conditional probability notation] $\\mathbb P(H\\mid e).$',
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