I checked with a friend who has a PhD in statistics specifically about this Twitter thread (which was referenced in some of the articles about this): https://tw

I checked with a friend who has a PhD in statistics specifically about this Twitter thread (which was referenced in some of the articles about this): https://twitter.com/wfithian/status/1252692357788479488 https://twitter.com/wfithian/status/1252692357788479488 One claim Will Fithian makes is: > The errors are not debatable and can be seen in these two screenshots of the supplement: 0.0034, the standard error meant to measure uncertainty about prevalence pi, is not the square root of 0.039, and the variance of a binomial estimate of proportion depends on the sample size. My statistician friend says: > In fact the math checks out in favor of the authors. Square root of .039, then divide by square root of 3330. .= 0034 just like reported. > So the error is debatable. > Now, sometimes you should be using the standard deviation, not the standard error, but that isn't his claim. The .0034 is absolutely the correct standard error, unless there is a difference in terminology for the field or something.