1. A test for a certain disease is found to be 95% accurate, meaning that it will correctly diagnose the disease in 95 out of 100 people who have the ailment. The test is also 95% accurate for a negative result, meaning that it will correctly exclude the disease in 95 out of 100 people who do not have the ailment. For a certain segment of the population, the incidence of the disease is 4%. (1)r (Hint: define appropriate events and use Bayes Theorem): (2) person actually has the disease, given that the test is positive; (3) correct. Hence, You can conclude that there is only a much smaller probability to claim "the person really has the disease" after knowing that "the test is positive", though the test has 95% "correctness". Explain this difference. If a person tests positive, find the probability that the person actually has the disease Now suppose the incidence of the disease is 49 . Compute the probability that the The probability you obtained in (1) is much smaller than 0.95, if your computation is Medical Science De EE S4