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(B)
P(A) 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(B)
= P(B). This means that the
P(A) P(A)
occurrence of event B first did not affect the probability of event A occurring next
P(A and B) P(A).P(B)
When two separate events, A and B, are independent, P(BA) =
PA)
P(A)
occurrence of event A first did not affect the probability of event B occurring next.
P(B). This means that the
P(A).P(B)
P(A)
When two separate events, A and B, are independent, P(BA) =
P(A and B)
P(A)
occurrence of event B first affected the probability of event A occurring next.
- P(B). This means that the