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Which statement best explains conditional probability and independence?

 

A: When two separate events, A and B, are independent, P(A|B)=P(B) . This means that the probability that event A occurred first has no effect on the probability of event B occurring next.

 

B: When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A)=P(B) and P(A|B)=P(B) .

 

C: When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A)=P(B) and P(A|B)=P(A) .

 

D: When two separate events, A and B, are independent, P(A|B)=P(A) . This means that the probability that event B occurred first has no effect on the probability of event A occurring next.

 Apr 21, 2018
 #1
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D: When two separate events, A and B, are independent, P(A|B)=P(A) . This means that the probability that event B occurred first has no effect on the probability of event A occurring next.

 

 

cool cool cool

 Apr 21, 2018

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