I stumbled across the analysis below. Without wanting to be political, I'm sure that there is some valid explanation, but I'm curious. They Jupyter notebooks on github here: https://github.com/cjph8914/2020_benfords seem to show discrepancies in electoral data in Alleghany PA, Chicago IL, and Milwaukee WI. What is missing from their analysis? Is there a way to explain this (bad data, bad analysis, etc)? Should oddities be examined more closely?
Ask HN: Benford's Law and 2020 Presidential Election
1–10 of 16 posts
Re: Ask HN: Benford's Law and 2020 Presidential Election
#2See the following below for a quick visual summary:
Some people may be in for a rude awakening should audits occur.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#3There's some real questions that should be answered, no matter how you lean. The following link was shared to me giving a quick summary of this:
imgur.com/a/gxuVAxc
I mean if everything's fine then somebody should be able to explain why this isn't an issue, right?
And there's also the infamous and mostly censored "4am vertical spikes":
imgur.com/a/TwZqBQ7
I just want an explanation without being censored. These are reasonable questions to have answered, and until they are, I definitely have some doubt in what's being reported.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#4From a comment:
> This repo is attempting to apply Benford's Law to vote count distribution, so that's what actually needs to span multiple orders of magnitude. Precinct distribution is a factor in vote count distribution but it doesn't tell the whole story. I don't see the Milwaukee data in this repo, but take a look at the Chicago data: https://github.com/cjph8914/2020_benfords/blob/main/data/chi... Biden's vote totals are solidly contained within one order of magnitude, the 100-999 range. Trump's vote totals range from single digits into the hundreds, across three orders of magnitude. Jo Jorgensen is mostly in the 0-20 range, across two orders of magnitude.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#5There's some real questions that should be answered, no matter how you lean. The following link was shared to me giving a quick summary of this: imgur.com/a/gxuVAxc I mean if everything's fine then somebody should be able to explain why this isn't an issue, right? And there's also the infamous and mostly censored "4am vertical spikes": imgur.com/a/TwZqBQ7 I just want an explanation without being censored. These are r…
You are not the only one. I'm curious as well. I always expect a few statistical oddities per election year, but there was a whole lot more than I usually recall hearing about this year.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#6I don't know enough about Benford's law to draw conclusions, but is N=O(1000) a large enough sample size to expect it to apply? My intuition suggests that if county size does not span enough orders of magnitude then Benford's wouldn't apply because the distribution might lie in one of the "spikes" of the Benford curves, rather than reflecting the average. For example, if many counties had a population size starting with a "4", you'd expect more vote counts to start with "2" (presuming each candidate received close to 1/2 of the votes).
Hopefully someone with a stronger math background can expand in a more fluent way :)
Re: Ask HN: Benford's Law and 2020 Presidential Election
#7From a comment: > This repo is attempting to apply Benford's Law to vote count distribution, so that's what actually needs to span multiple orders of magnitude. Precinct distribution is a factor in vote count distribution but it doesn't tell the whole story. I don't see the Milwaukee data in this repo, but take a look at the Chicago data: https://github.com/cjph8914/2020_benfords/blob/main/data/chi... Biden's vote to…
The pattern holds true even in 3 digits order of magnitude. The link I shared shows an analysis for 2nd digit Benfords as well, where Biden's is suspect and his opponent's is not.
imgur.com/a/gxuVAxc
Plus there are numerous other examples across different states with the same patterns, which is troubling.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#8I don't know enough about Benford's law to draw conclusions, but is N=O(1000) a large enough sample size to expect it to apply? My intuition suggests that if county size does not span enough orders of magnitude then Benford's wouldn't apply because the distribution might lie in one of the "spikes" of the Benford curves, rather than reflecting the average. For example, if many counties had a population size starting w…
Yes, you would still expect Benford's law to apply with 3 orders of magnitude.
The real suspicious fact is that even within smaller totals, Biden's opponent's numbers comform to Benford while his do not.
Re: Ask HN: Benford's Law and 2020 Presidential Election
#9Swolgenix XL
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Re: Ask HN: Benford's Law and 2020 Presidential Election
#10From a comment: > This repo is attempting to apply Benford's Law to vote count distribution, so that's what actually needs to span multiple orders of magnitude. Precinct distribution is a factor in vote count distribution but it doesn't tell the whole story. I don't see the Milwaukee data in this repo, but take a look at the Chicago data: https://github.com/cjph8914/2020_benfords/blob/main/data/chi... Biden's vote to…
Why is NewRecruit’s reply dead?
NewRecruit 6 minutes ago [dead]
The pattern holds true even in 3 digits order of magnitude. The link I shared shows an analysis for 2nd digit Benfords as well, where Biden's is suspect and his opponent's is not.
imgur.com/a/gxuVAxc
Plus there are numerous other examples across different states with the same patterns, which is troubling.