Rhomboid, let me put it another way. A man has two children.Okay, two children. Each has a 50/50 chance of being male or female. This makes four possible combinations, each equally likely to happen - so each has an equal 25% chance of happening.
We start by observing one of the children at random, and note that it is male.Okay, since we know that one of the children is male, this eliminates one of the four possible outcomes. But this is all the the knowledge tells us. It does not change anything else, there are still three possible outcomes each with a 1 in 3 chance of happening.
This is obviously more likely in the case where both children are male.And this is where you stop making logical sense. The "male/male" state is still just one of the three remaining possibilities. It does not become any more likely to happen than it was before, so the chances of the other child being female are still 2 out of 3, corresponding to the 3 equally possible outcomes.
Someone has prepared two envelopes containing money. One contains twice as much money as the other. You have decided to pick one envelope, but then the following argument occurs to you: Suppose my chosen envelope contains $X, then the other envelope either contains $X/2 or $2X. Both cases are equally likely, so my expectation if I take the other envelope is .5 * $X/2 + .5 * $2X = $1.25X, which is higher than my current $X, so I should change my mind and take the other envelope. But then I can apply the argument all over again. Something is wrong here! Where did I go wrong?One from the probability section:
Suppose that it is equally likely for a pregnancy to deliver a baby boy as it is to deliver a baby girl. Suppose that for a large society of people, every family continues to have children until they have a boy, then they stop having children. After 1,000 generations of families, what is the ratio of males to females?Most of the problems already mentioned, if not all, are contained within, along with solutions.
Suppose that a test for a particular disease has a very high success rate:I'm completely confused by the boy/girl problem. Thanks, guys!
* if a tested patient has the disease, the test accurately reports this, a 'positive', 99% of the time (or, with probability 0.99), and
* if a tested patient does not have the disease, the test accurately reports that, a 'negative', 95% of the time (i.e. with probability 0.95).
Suppose also, however, that only 0.1% of the population have that disease (i.e. with probability 0.001). We now have all the information required to use Bayes' theorem to calculate the probability that, given the test was positive, that it is a false positive...
Despite the apparent high accuracy of the test, the incidence of the disease is so low (one in a thousand) that the vast majority of patients who test positive (98 in a hundred) do not have the disease.
Three men stay at a hotel for the night. The innkeeper charges thirty dollars per room per night. The men rent one room; each pays ten dollars. The bellhop leads the men to their room. Later, the innkeeper discovers he has overcharged the men and asks the bellhop to return five dollars to them. On the way upstairs, the bellhop realizes that five dollars can't be evenly split among three men, so he decides to keep two dollars for himself and return one dollar to each man.The answer here. Many more such puzzles at Brainfood (a wonderful site for puzzles).
At this point, the men have paid nine dollars each, totalling 27. The bellhop has two, which adds up to 29. Where did the thirtieth dollar go?
posted by flabdablet at 10:00 PM on March 21, 2006