Discussion
Which quantity does conditioning on evidence produce?
Answer: C
The posterior is what Bayes' rule computes: the probability of the hypothesis given the evidence, combining the prior with how likely the evidence would be under that hypothesis. The probability of evidence given hypothesis is the likelihood, which is a different quantity pointing the other way. Timing and completeness are unrelated. Keeping the two directions distinct is the single most important discipline in applying the rule. A limit that survives making every external component ideal is an intrinsic one, and worth knowing for that reason.
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