  In the example discussed above, the condition that J. Doe died during 2000 is a fairly strong predictor of senior citizenship.  Indeed, the equation PH(E) = 0.57 tells us that 57% of the total deaths occurred among seniors that year.  Bayes' theorem lets us use this information to compute the "direct" probability of J. Doe dying given that he or she was a senior citizen.  We do this by multiplying the "prediction term" PH(E) by the ratio of the total number of deaths in the population to the number of senior citizens in the population, P(H)/P(E) = 2.4M/16.6M = 0.144.  The result is PE(H) = 0.57 × 0.144 = 0.082, just as expected.