# Calculating standard error for a Normal population

I'm a programmer, with a decent but not-expert knowledge of stats, and I'm working through these instructions for how to create funnel plots.

I understand from a previous question that the standard error in these instructions is being calculated using p(1-p) (in step 4), because these are events and therefore follow a Bernoulli distribution.

However, if the data was about individuals in the population, rather than events, how would I calculate the standard error?

I know it would be a Normal distribution and therefore standard error would be the square root of the standard deviation, but what formula would I calculate that, given the data I have in the example? (i.e. a set of samples with denominator and numerator population).

Thanks for your help.

## 1 Answer

This is true for any continuous distribution and not just a normal. You simply calculate the sample standard deviation and divide it by the square root of n.

Let m be the the mean for the sample sum the squared deviations of the observations Xi for the sample mean m divide by n-1 (of the unbiased variance estimate) and take the square root for the sample standard deviation estimate. Then divide by the square root of n to get the standard error.