Another way to look at it is this way: P(H|D) = P(D|H) P(H) / P(D) Bayesians are interested in the probablity of various hypotheses h in H given some data D.

Another way to look at it is this way: P(H|D) = P(D|H) P(H) / P(D) Bayesians are interested in the probablity of various hypotheses h in H given some data D. Frequentists calculate the probability of some data given a hypothesis (p-value is not strictly a probability but it can be one - it is ALWAYS a measure of extremity of data coming from the assumed hypothesis, which can be considered a relative probability). Most interesting to me is that the Bayesian formula includes P(D|H) which is basically what the frequentists are calculating. In this sense, the question Bayesians answer is far closer to what we want to ask and far more powerful. In practice, the frequentist approach is often more than enough, though. The tradeoff is computability and simplicity.