*apparently*
(smdh for not remembering this properly)
the same test can have a false positive rate of near 0% (say you have a great test and/or are testing only very very sick patients in a overwhelming outbreak eg Mexico)
or near 100% (say testing COVID19 in New Zealand)
a critical number to know is:
what is the chance that if you test someone who is negative, what is the chance they tests positive.
if you can this x then you multiply this by the number of tests N and then you know the # of false positives...
does anyone remember that term? 
-
-
I think the worse are the false negative, because they still going around infecting others ... https://www.mathsisfun.com/data/probability-false-negatives-positives.html …
-
yes you are right but the meme running around (because elon said it)
is that a lot of tests are false positives and i'm trying to outrace the misunderstanding.
End of conversation
New conversation -
-
-
The value you're calculating is the *positive predictive value.* (Or *negative predictive value* for the predictive power of a negative test result in the presence of false negatives.) The prevalence in the sample population against which these are measured is the *base rate*.
Thanks. Twitter will use this to make your timeline better. UndoUndo
-
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.
