Lies, damned lies, and statistics
By: Friendly Fire
Tags: Facts, Debunk, Statistics, Election 2020

In recent days I have noticed a stream of related claims on Twitter regarding claims of either outright vote-rigging, or “statistical anomalies” regarding the vote count in a number of different states in the 2020 US Elections.

The Claims

These claims have taken a number of different forms — an article on The Spectator’s US site here says

In Georgia, Biden overtook Trump with 89 percent of the votes counted. For the next 53 batches of votes counted, Biden led Trump by the same exact 50.05 to 49.95 percent margin in every single batch.

Elsewhere, in this post, the author makes the same claim :

President Trump was up by as much as 57% to Biden’s 42%.

The Drop: Then dumps of unexplained ballots given to Biden for hours until Joe Biden takes the lead.

The Roll: Then for the next 53 batches of votes counted, EVERY SINGLE vote batch had exactly a 50.05% to 49.95% victory margin for Biden.

On Twitter, @redpillx2 claims to have uncovered votes being moved to and from Biden, Trump and third parties And in a video interview on Periscope, the same claims are made in a discussion between Dr. Shiva Ayyadurai and others.

The Data

All the claims appear to be based, at least according to the spreadsheets illustrating the second article linked to above, on the publicly available data disseminated by Edison Research. This was used by various organisations such as newspapers and television outlets to keep. This data is still available online in JSON form, and can be retrieved and parsed into spreadsheet form for ease of reference.

A typical update will look like this :

[531] => Array (

[vote_shares] => Array

( [bidenj] => 0.505

[trumpd] => 0.479)

[votes] => 5523742

[eevp] => 99

[eevp_source] => edison

[timestamp] => 2020–11–09T21:42:13Z

)

From this can only be drawn the following information — the time the update was posted, the number of votes counted at the point in time at which the update was posted, and the overall percentage of all the votes split between the two candidates. One can reliably extract the number of votes counted since the last update by subtracting the number of votes, but that is it.

The problem

The fundamental problem, though, is that the people pushing the claims of “rigging” have extrapolated that data, and either do not realise, or choose to overlook, what it is that the spreadsheet they end up with is telling them.

Take, for example, this screenshot from the second article linked to above (which is probably one of the original sources for the other sites making similar claims) :

If we label the columns A, B and so on, only columns A, C, D and F are actually contained in the publicly available data. Column A is the timestamp of the update, C and D are the vote share of Democrats / Republicans, and F is the total votes cast.

Columns B (Trump’s votes in 2016), G (total votes in 2012) and H (total votes in 2016) are static and not relevant for this purpose. Column E (vote share of third party) is equal to 1 minus Columns C and D, and is reliable.

All the columns beyond that, however, are extrapolated. And it’s at this point that the claim begins to break down.

Columns I, J and K claim to show, respectively, the votes for Democrats, Republicans, and Democrats and Republicans combined. Columns I and J are obtained by multiplying the total number of votes cast by the relevant party’s vote share, and Column K is the sum of the previous two columns. The giveaway is that the numbers are not whole numbers. If these numbers were actually in the publicly available data, they would not be given to three decimal places.

This is when the wheels really come off.

Ignore the next two columns, and move on to the “Incremental vote for Democrats / Republicans” shown by Columns N and O. These purport to show the number of votes cast, since the last update, for each candidate. But that information is not provided in the underlying data. If an update covers 200 votes, there is absolutely no way to determine with accuracy how many of those votes were for one candidate or the other other than for the very first update of the night.

So the spreadsheet instead draws this conclusion by comparing the votes for each party in columns I and J (remember, though, these numbers are extrapolated from the overall vote share) against the same figures for the previous update.

Finally, in the two coloured columns, the spreadsheet then shows the percentages of the figured in columns I and J. And this is where the claim comes in — in the screenshot above, the percentage for each update remains the same, a consistent 50.051 / 49.49 split, for a large number of updates.

Of course it does — because that’s what it’s been told to do. All of the numbers past the total number of votes cast in Column F are extrapolated from the overall vote share of the candidates in Columns C and D. Only when these figures change — as they do in one place on the screenshot above, will the figures in the last two columns change.

Conclusion

No, the data does not show statistically improbable vote counts. It does not show votes being laundered between candidates. It does not show fraud, ballot rigging, or other nefarious activity.

All it shows is that some people shouldn’t be trusted with Excel.