Biden's vote data is far more anomalous than Trump's

Twitter ^ | November 5, 2020 | statsguyphd

[karpov]

I am making these tweets to explain in one place some analysis that was done last night. 1 - I was asked offline about doing Benford's on election data. I explained that this is common and a useful way to detect anomalies in data that are driven by artificial process (e.g. fraud)

2 - My student then pointed me towards a tweet that was exploring this type of analysis (but they hadn't done Benford's). So I chimed in.

3 - However, I did not know what data they used so I found a source for the context they referenced. However, I could not initially find write-ins versus non-write-ins, so I looked at candidate counts.

4 - I then wrote a quick script to gather that data, here is an example of what the data gathering portion of this process looked like.

6 - I wrote the code to produce the Benford's discrete distribution. This code looks like this.

7 - Now that I had the data and the distribution, I simply needed to perform the test. To do that, I leveraged scipy's chisquare. However, prior to doing that, you need to produce the expected result values (not just the percentages. But this is as simple.

8 - To do that, you take the total number of observations (number of numbers that the first digit counts are derived from) and multiply them by the Benford's distribution frequencies accordingly. This looks like this:

[lodi90]

Never Trump ticket splitting is real.

[dfwgator]

Of course, if you point that out to a liberal, they’ll say that Ohio must have cheated, since they were the only of those States with the GOP observing the election.

[cgbg]

Here in CT the Democratic blowout (way above historical averages) went all the way down ticket to the Congressional races. However, it did not include the state legislative races.

That was pure fraud—there is no way that high percentages of Democrats and/or Independents didn’t bother to vote in the state races.