What do you expect to happen if a precinct in a big city which often votes 85%+ for the democrat reports mail in ballots, and based on pre-election polling, there was something like a 75% democrat to 25% republican preference for mail in voting, and you had state laws that prevented mail in ballots to be opened prior to election day?
I think we were incredibly fortunate how telegraphed all this was. Imagine how much more compelling this all would be if DJT hadn’t spent the months leading up to the election saying exactly how he intended to undermine any unfavorable result.
I actually skimmed the link, it’s dumber than that. They are arguing is that it is shocking that Biden won a number of large precincts by large amounts, while Trump didn’t win any large precincts by similar amounts. Breaking news: urban precincts have more voters than rural ones, and tend to vote Democratic.
The author is claiming that the large tranches in favor of Biden are unreasonable outliers, that are not found in other states. This is an interesting claim, I think but I’d need a lot more data than what he offers – a few unconvincing scatter-plots and a national ranking of tranches, with WI, MI, PA around the top of the ranking.
It would be more convincing if the researcher talked more about these tranches instead of just treating them as statistics (why and where and when specifically do they occur) and if he showed some more national data (how common are big tranches and how do they relate to swing states, mail voting, urban districts, etc.) and data from other elections to give it broader context.
In other words, if I were actuarying, this would be the beginning of a project-- not the end of a project.
As it stands it’s a sort of thing that I might look into if I were Nate Silver and was drunk and bored and alone on a Saturday because of covid.
Great. Another thread soon to be deleted by the OP, because the math being supported by an alleged actuary is so horrifying that it stands to ruin his credentialed standing.
I’ll let the more competent and driven actuaries tackle this. Or, just click the disproving links they find via Google.
article is saying that the ~500k Biden votes that were ‘dumped’ into the count in the early hours of Nov 4 are suspicious because it is unlikely that all of the most Biden heavy areas all posted at the same time. Without further context, it looks suspicious, but I recall bitching and moaning about the manner vote tallies were updated all night and nothing should be derived from it.
So a validating article for those still angry over the loss, but nothing more.
Mail in ballots broke towards Biden regardless of the county. There were never going to be Trump heavy areas posting a large chunk of mail in ballots. Those are what were being counted in the early hours of Nov 4 because some states did not allow them to be counted earlier. PA was one of those states.
The basic intuition is: big margins are one thing, and so are super-skewed results, but it’s weird to have them both at the same time, as they generally become inversely related as either value increases.
Basic argument is that absolute differences in vote totals and ratios should be inversely related. I guess the unnamed authors assume that votes are cast randomly or that the proportionate mix of voters in all districts is identical…
This spurred to me actually have a read… it’s about as expected. How desperate is the guy to assume votes are random? This is why you’re made to state assumptions on exams.
I was almost thinking this exactly. In fact one thing I noted when everyone was griping about how long it took to count the votes in these battleground states was that none of the non battleground states had finalized their counts either. They were just called because the margin was so great. Specifically with the OP example I would ask to see what big batches of mail in ballots looked like across the country and compared to historical patterns of the same area and if it was available a poll to see how many people in each party were likely to vote by mail for the locale.