>"Consider this case: You have cancer. You can do nothing about it, and die in 3 months, or you can have an operation, that has a 60% chance of curing you, 30%

>"Consider this case: You have cancer. You can do nothing about it, and die in 3 months, or you can have an operation, that has a 60% chance of curing you, 30% chance of doing nothing, and 10% chance of killing you." I recommend everyone ask their doctor what a p-value means before listening to any stats like this. Here is just one of many horror stories about the poor understanding of stats that pervades medicine (TBH though, this is mostly the fault of stats education): "Nearly 40 years ago the New England Journal of Medicine published a short survey of doctors’ understanding of the results of diagnostic tests.1 The participants, all doctors or medical students at Harvard teaching hospitals, were asked, “If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing else about the person’s symptoms or signs?” This wasn’t a very difficult question, which made the results all the more shocking. Fewer than a fifth of participants gave the correct answer, and most thought that the hypothetical patient had a 95% chance of having the disease. Of course, this was a long time ago, and medical curriculums now contain much more in the way of statistics and probabilistic reasoning. You might expect that if the exercise were repeated today almost everyone would give the right answer. But you’d be wrong. Earlier this year a similar study was carried out, also in hospitals in the Boston area of Massachusetts, and the results were no better.2 Most doctors who were asked exactly the same question thought that the patient had a 95% chance of having the disease." http://www.bmj.com/content/349/bmj.g5619 http://www.bmj.com/content/349/bmj.g5619