Conditional Probability
The conditional probability of an event B will be the probability that the event will occur given the knowledge that an event A has already occurred. This probability is written P(B|A), notation for the probability of B given A. In the case where events A and B are independent to the conditional probability of event B given event A is simply the probability of event B, that is P(B)..
Let us consider the events A and B are not independent, then the probability of the intersection of A and B (the probability that both events occur) is defined by
P(A and B) = P(A)P(B|A).
From this definition, the conditional probability P(B|A) is easily obtained by dividing by P(A):
P(B|A)= P(A and B)/ P(A)
This expression is only valid when P(A) is greater than 0. This could also help us on digestive system diagram
The conditional probability of an event B will be the probability that the event will occur given the knowledge that an event A has already occurred. This probability is written P(B|A), notation for the probability of B given A. In the case where events A and B are independent to the conditional probability of event B given event A is simply the probability of event B, that is P(B)..
Let us consider the events A and B are not independent, then the probability of the intersection of A and B (the probability that both events occur) is defined by
P(A and B) = P(A)P(B|A).
From this definition, the conditional probability P(B|A) is easily obtained by dividing by P(A):
P(B|A)= P(A and B)/ P(A)
This expression is only valid when P(A) is greater than 0. This could also help us on digestive system diagram
