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Care to clarify? My understanding was that a 95% confidence interval implies the chance of a false positive of 5%. From http://www.mit.edu/~6.s085/notes/lectu
by rifung 7y ago
Care to clarify?
My understanding was that a 95% confidence interval implies the chance of a false positive of 5%.
From http://www.mit.edu/~6.s085/notes/lecture2.pdf http://www.mit.edu/~6.s085/notes/lecture2.pdf
"In particular, we can ask for an
interval around ˆp for any sample so that in 95% of samples, the true mean p will lie inside
this interval. Such an interval is called a confidence interval."
- Retric 7y agoSuppose you test for 1 true positive out of 1001 cases. You are likely to find the actual positive and 50 false ones. However, that’s with a single test. If you run 5+ different tests you are likely able to distinguish the true positive.
- 6gvONxR4sf7o 7y agoTo add to this, you can't just run 5+ tests. You have to run wholly independent ones.
- 6gvONxR4sf7o 7y agoThe false positive rate has nothing to do with positive examples (hugely counterintuitively). A false positive happens when there's nothing there but you think there is. The rate of these is compared to all incidents where there's nothing there. So it's the fraction of negative instances where you think there's a positive. No actual positives have to come into the picture.
- rifung 7y agoAh you're right that makes a lot of sense thanks for the explanation