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Sorry, you are correct. I'll update the problem.


I'll follow up by mentioning that even as you have it worded now, it's not precise enough to answer. You need to explicitly describe the false positive and negative rates separately. As is, a test that is just "return false" (100% false-negatives, 0% false-positives) will be 99% accurate, but gives no information, whereas a test with 1% false positive rate can have a 1% false negative rate and still be correct 99% of the time, and will provide much more information.

Statistics is weird and unintuitive.


I guess I should say that everyone takes the test. I'm not a statistician, I'm a mathematician. The way I understand the phrase, "the test is 99% accurate" is that this means: assuming everyone were to be tested then 99% of the time you get an accurate result. Thus .99(1%) = 0.99% of the people will correctly test positive and 0.01(99%) = 0.99% of the population will incorrectly test positive.


The problem still stands then.




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