  Suppose you're on a game show, and you're given the choice of three doors:
Behind one door is a car; behind the others, goats. You pick a door, say No. 1,
and the host, who knows what's behind the doors, opens another door, say No. 3,
which has a goat. He then says to you, ``Do you want to pick door No. 2?'' Is
it to your advantage to switch your choice? The answer is ``yes'' but the
literature offers many reasons why this is the correct answer. The present
paper argues that the most common reasoning found in introductory statistics
texts, depending on making a number of ``obvious'' or ``natural'' assumptions
and then computing a conditional probability, is a classical example of
solution driven science. The best reason to switch is to be found in von
Neumann's minimax theorem from game theory, rather than in Bayes' theorem.
