In Bayes' theorem, what is the posterior probability?
- The likelihood of the evidence
- The probability of an event before evidence is observed
- The probability of the evidence given the event
- The updated probability of an event after evidence is observed
In Bayes' Theorem, the posterior probability is the updated probability of an event after new evidence has been observed. It is calculated by multiplying the likelihood and the prior probability and then dividing by the probability of the evidence.
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