Which statement best explains conditional probability and independence? When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event B first did not affect the probability of event A occurring next.
When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event A first affected the probability of event B occurring next.
When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event A first did not affect the probability of event B occurring next.
When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event B first affected the probability of event A occurring next.