  To illustrate, suppose J. Doe is a randomly chosen American who was alive on January 1, 2000.  According to the United States Center for Disease Control, roughly 2.4 million of the 275 million Americans alive on that date died during the 2000 calendar year.  Among the approximately 16.6 million senior citizens (age 75 or greater) about 1.36 million died.  The unconditional probability of the hypothesis that our J. Doe died during 2000, H, is just the population-wide mortality rate P(H) = 2.4M/275M = 0.00873.  To find the probability of J.  Doe's death conditional on the information, E, that he or she was a senior citizen, we divide the probability that he or she was a senior who died, P(H &amp; E)  = 1.36M/275M = 0.00495, by the probability that he or she was a senior citizen,  P(E) = 16.6M/275M = 0.06036.  Thus, the probability of J. Doe's  death given that he or she was a senior is PE(H) = P(H &amp; E)/P(E) = 0.00495/0.06036 = 0.082.  Notice how the size of the total population factors out of this equation, so that PE(H) is just the proportion of seniors who died.  One should contrast this quantity, which gives the mortality rate among senior citizens, with the "inverse" probability of E conditional on H, PH(E) = P(H &amp; E)/P(H) = 0.00495/0.00873 = 0.57, which is the proportion of deaths in the total population that occurred among seniors.