HackerThe medical test paradox, and redesigning Bayes' rule
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In the talk’s hypothetical cohort, screening produces nine true positives and 89 false positives. Interpreting a positive means counting among all positives, rather than among everyone with the condition.
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And then suppose that among the remainder without cancer, 89 get false positives, and 901 correctly get negative results.So the probability that she's in the cancer group given the test result is 9 divided by 9 plus 89, which is approximately 1 in 11.