Share

## Which statement best explains conditional probability and independence? When two separate events, A and B, are independent, P(A

Question

Which statement best explains conditional probability and independence?

When two separate events, A and B, are independent,

P(A and B) P(A).P(B)

P(BA)

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.

When two separate events, A and B, are independent,

P(A and B) P(A).P(B)

P(BA)

– P(B) This means that the

P(A)

P(A)

occurrence of event B first affected the probability of event A occurring next.

When two separate events, A and B, are independent,

P(A and B) P(A.P(B)

P(BA)

P(B)

P(A)

This means that the

PA

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(A and B) P(A).P(B)

P(BA)

P(B)

P(A)

P(A)

This means that the

in progress
0

Mathematics
1 year
2021-08-02T06:02:40+00:00
2021-08-02T06:02:40+00:00 1 Answers
22 views
0
## Answers ( )

Answer:The answer of the question would be: C)

Step-by-step explanation: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.