The following excerpt is from Unweaving the Rainbow (1998) by Richard Dawkins.
A recent highly publicized case in America, where the jury were systematically confused about DNA evidence, has also become notorious for another piece of bungled probability theory. The defendant, who was known to have beaten his wife, was on trial for finally murdering her. One of the high-profile defence team, a Harvard professor of law, advanced the following argument: Statistics show that of men who beat their wives, only one in 1000 go on to kill them. The inference that any jury might be expected to draw (indeed, were intended to draw) is that the defendant’s
beating of his wife should be discounted in the murder trial. Doesn’t the evidence show overwhelmingly that a wife-beater is unlikely to turn into a wife murderer?
Do the following in order to expose this misleading defence argument.
(a) Draw a Venn diagram with S defined as the set of all wives, B as the subset of wives that are beaten by their husbands, M as the subset of wives that are murdered, and H as the subset of wives that are murdered by their husbands.
(b) Using the symbols defined above, write down the conditional probability that the defence counsel put forward.
(c) Since we know that someone has murdered his wife, write down the pertinent conditional probability that should have been used.
(d) Provide an algebraic proof that the probability in (c) is greater than or equal to that in (b). Hint: Look at the Venn diagram from (a). (How much more incriminating might this larger probability have been?)
---------------
This is what I have so far, but I'm not sure if I'm going in the right direction.
(a)

(b) P(H|B) = P(H intersect B)/P(H)
(c) P(H|M) = P(H intersect M)/P(H)
(d) algebraic proof...a bit lost here