According to Bayes' Rule, the probability that they patient has measles given that he has red spots p(H|E) is

• Proportional to the probability of a patient developing red spots when he has measles, denoted by p(E|H)
• Proportional to the probability of developing measles in general.
• Inversely proportional to the probability of developing red spots in general.

Given this information, If the probability of developing red spots when a person has measles is 99%, how will this affect the diagnosis? On the other hand, let's assume hypothetically that only 1% of those who have measles develop read spots. In this case, how will that affect P(H|E)? Overall, is the patient more or less likely to be diagnosed with measles?