Question

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.

Answer 1

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.

Answer 2

The answer of the question would be:

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.

Because of the evident independence.