Bayes' theorem is expressed as P(A|B) = [P(B|A) × P(A)] / P(B). Here, P(A) is called the:

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In Bayesian inference, P(A) is the prior probability, representing initial belief about hypothesis A before observing evidence B; P(A|B) is the updated posterior probability.

Bayes' theorem is expressed as P(A|B) = [P(B|A) × P(A)] / P(B). Here, P(A) is called the: MCQ with Answer and Explanation

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