Which statement best explains conditional probability and independence?
A) When two separate events, A and B, are independent, P (A|B) = P (A). This means that the probability of event B occurring first has no effect on the probability of event A occurring next.
B) When two separate events, A and B, are independent, P (B|A) ≠P (A|B). The probability of P (A|B) or P (B|A) would be different depending on whether event A occurs first or event B occurs first.
C) When two separate events, A and B, are independent, P (A|B) = P (B). This means that the probability of event B occurring first has no effect on the probability of event A occurring next.
D) When two separate events, A and B, are independent, P (A|B) ≠P (B|A). This means that it does not matter which event occurs first and that the probability of both events occurring one after another is the same.
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