Suppose that 1% of all people have a particular disease. A test for the disease is 99% accurate. This means that a person who test positive for the disease has a 99% chance of actually having the disease, while a person who test negative for the disease has a 99% chance of not having the disease.
If a person tests positive for the disease, what is the chance (rounded to the nearest hundredth) that he or she actually has the disease?
I have worked the problem two ways and am receiving two different answers.
A complete worked through example of a probability problem involving Bayer's theory.