If the election count is say, 48% for A and 50% for B and 2% other, that's that. You don't have error bars, you don't have student-t tests, you don't have random varaibles, you don't have "confidence intervals". You assume you have the ground truth. You have a precise number assumed to be without error.

Its actually a fundamentally different kind of math than what is typically taught in statistic classes (standard error vs standard deviation. R-values, random variables, etc. etc.)

When it comes to "total population" style information gathering, the questions of reliability are about whether-or-not you in fact, grabbed the total population... and nothing really "mathematical" (such as what are my 95% confidence interval?)

---------

When people say 600,000 died of COVID19 in the USA, there's no error bar, standard deviation, or random variable on that number. It is what it is: the ground truth according to a particular source.

And when you have a 2nd source of information with slightly different numbers (ex: State databases vs US level databases), you have a non-mathematical problem for how to resolve the apparent contradiction.

There's no "metastudy" over other surveys. There's no "resample again", there's no reproducibility. These statistical concepts and tests simply do not apply. If you do in fact decide to conduct a 2nd census, you will find that the numbers will differ in practice (ex: recounting the same set of ballots a 2nd time). But there's no underlying mathematical model for why this happens, as is the case in typical population statistics (student t-test assumes a standard error over a standard deviation of a hypothetical sample, etc. etc.)