# Calculating standard error for funnel plots

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 know that there are better ready-made tools (e.g. R) for generating funnel plots, but these instructions are helping to understand the basics of funnel plots.

So, my question: Step 4 in the instructions refers to a 'special kind' of standard error. Why is it special?

And, can I validly copy the way standard error is calculated in these instructions to build a funnel plot for any dataset that includes raw population count and raw incident count?

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Generally a variance for a mean of $n$ iid $X_i$s is ${\rm var}(X_i)/n$. Now since the $X_i$s are Bernoulli with success probability $p$, ${\rm var}(X_i)$ has a special form. It is $p(1-p)$. So each of the $23$ means have variance of the special form $p(1-p)/n$ and the standard error is the square root of that.