Final answer:
The conditional probability of A given B under the measure P0[B] is equal to the probability of A under the measure P0.
Step-by-step explanation:
Let's assume there are two events A and B, with P(B) > 0. We need to show that P[A|B] = P(A) for the measure P0[B](A|B). In other words, we want to prove that the conditional probability of A given B under the measure P0[B] is equal to the probability of A under the measure P0.
Using the definition of conditional probability, we have:
P[A|B] = P[A AND B] / P[B]
But since P0[B](A|B) is defined as P[A AND B] / P0[B](B), we can rewrite the equation as:
P[A|B] = P0[B](A|B) / P0[B](B)
Since B is the sample space under P0[B], the probability of B under the measure P0[B] is equal to 1. Therefore, we can simplify the equation to:
P[A|B] = P0[B](A|B) / 1 = P0[B](A|B)
Thus, we have shown that P[A|B] = P0[B](A|B), which means that the conditional probability of A given B under the measure P0[B] is equal to the probability of A under the measure P0.