4 ms·
There's a general principal involved, that once you start throwing round numbers like 'one in a million' around, you're almost certainly overlooking larger so
by ajb 3y ago
There's a general principal involved, that once you start throwing round numbers like 'one in a million' around, you're almost certainly overlooking larger sources of error. Eg, someone fucking up in the lab is much more likely than one in a million. There was a famous case where they were looking for (what they thought was) a serial killer who showed up in a bunch of DNA tests, and it turned out to be some factory worker who had contaminated the swabs.
- jerf 3y agoI think of it as the "noise floor" of probability. It's great that, say, the odds of a DNA match is one in a trillion, but the odds of someone getting there wrong sample, misreading the results, deliberately forging the results, etc. is so much higher that the probability really only tops out (or bottoms out, depending on your perspective) at the noise floor. Comes up a lot in our world because computers so easily generate those large probabilities by being the things that can run millions of "samples" of some distribution per second, but you always have to cap those analyses to the probability noise floor or you'll be very misled.
- alexpetralia 3y agoThis is basically Bayes rule: the probability we have an accurate test given perfect conditions. But what is the baseline rate of perfect conditions? If it's less than 1, then our "posterior" probability will not be one in a trillion anymore, but something far less.
- ArnoVW 3y agoIf memory serves, the police were using swabs that was marked sterile but not rated "for use in forensics"
- ajb 3y agoYes, you are correct. The case is this one: https://en.wikipedia.org/wiki/Phantom_of_Heilbronn https://en.wikipedia.org/wiki/Phantom_of_Heilbronn