Question

Help

Answer 1

Could someone explain the meaning of these statements.

\[P(A|B) = P(A)\] if A&B are independent.

Answer 2

has to do with probability, the probability of an event say A given that B is true = probability of A.

Answer 3

yes - what is the question?

Answer 4

\[P(A|B) = P(A), IF A~and~B~are~independent~events \]

Answer 5

@welshfella

Answer 6

In probability theory, a conditional probability measures the probability of an event given that (by assumption, presumption, assertion or evidence) another event has occurred.[1] If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(A|B), or sometimes PB(A). For example, the probability that any given person has a cough on any given day may be only 5%. But if we know or assume that the person has a cold, then they are much more likely to be coughing. The conditional probability of coughing given that you have a cold might be a much higher 75%
Wikipedia
Hope it helps a little

Answer 7

If A and B are independent events the fact that B occurs has no effect on P(A)
therefore in this case P(A|B) = P(A)

Answer 8

Okay thanks guys!