Only 8 percent of the physicians got this correct.
Only 8 percent of the physicians got this correct. These sorts of misunderstandings can have huge effects on people’s pocketbooks and emotional. Assume breast cancer affects 0.8 percent of the female population between 40 and 50 years of age. There are two kinds of positive test results: true (the test indicates you do have it, and you actually have it) and false positives (the test indicates you do have it, but you really do not). Assume mammograms are 90% accurate at detecting people who have breast cancer (true positive), and are 93% accurate at spotting people who do not have breast cancer (true negative):a) false negative rate = b) false positive rate = c) In 1 M patients, the number with breast cancer is about d) Using result a), the number of patients with breast cancer who test positive = e) In 1 M patients, the number without breast cancer is about f) Using result c, the number of patients without breast cancer who test positive = g) Using results b & d, if your patient tests positive, the likelihood the patient indeed has the disease h) Another interesting problem is given that a women tests negative, what is the probability she actually has the cancer.
