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When events depend on each other
Conditional probability measures the chance of A given that B occurred: P(A∣B)=P(A∩B)/P(B). This appears constantly in quant interviews. Example: you flip a biased coin.
Given that you saw 5 heads in a row, what's the probability the coin is unfair? You'll use conditional probability to update beliefs as new information arrives.
