So, out of 100 women, 9.9 will test positive but be negative, and 0.8 will test positive and be positive. So if you are a forty-year-old woman and test positive, chances are much greater it’s a false positive (0.8 true positive / 10.7 total positive x 100 = 7.5%). This situation is analogous to the p-value. Having a p-value of 0.05 does not mean there is a 95 percent chance the hypothesis is true any more than a positive mammogram in a forty-year-old woman means there is a 90 percent chance she has breast cancer. Just as with breast cancer, you have to know what the base rate is.
