content: That reminds me of an interesting study they had on doctors and statistical understanding.  Ten out of every 1,000 women have breast cancer. Of these 10 women with breast cancer, 9 test positive. Of the 990 women without cancer, about 89 nevertheless test positive. A woman tests positive and wants to know whether she has breast cancer for sure, or at least what the chances are. What is the best answer?   The vast majority of doctors miss that question even in that very pedantic form. In reality it should also be able to be derived from these three points:  The probability that a woman has breast cancer is 1% ("prevalence") If a woman has breast cancer, the probability that she tests positive is 90% ("sensitivity") If a woman does not have breast cancer, the probability that she nevertheless tests positive is 9% ("false alarm rate")  When phrased that way more than half said it was 90% likely that a person who tests positive has breast cancer has it, and only 21% gave the correct answer.    That article also goes into misleading marketing for commercialized medicine, and "early detection." On the topic of breast cancer, 4 out of 1000 screened women will die from breast cancer. 5 out of 1000 unscreened women will die from breast cancer. This is a difference of less than 1 in 1000 but is marked as a "20% reduction in mortality" leading people to believe that if you take 1000 people, 200 lives will have been saved by early cancer screening. Yay for mixing profit and healthcare. What could go wrong?