The analysis just looks at the reported numerical values for each precinct. As an example, if precinct A reported 1200 votes for President Trump, and 3900 votes for Joe Biden, the size of the bar in the chart for President Trump for an X value of 1 would increase by 1 unit.
Similarly, in the chart for Joe Biden, the size of the bar in that chart with an X value of 3 would increase by one unit.
The analysis just looks at a set of numbers to see how they relate to an expected pattern found in many instances. The original physical meaning of the data is unimportant.
To see a graphical presentation of data and say the original meaning of it is unimportant is horrifying. This is how the media bamboozles data-ignorant America with plots, charts, and other half-baked statistics (exhibit A: everything related to COVID). Understanding WHAT is being captured in any graphic is extremely important, both for validating the legitimacy of the graphic (and its conclusions) and for being able to explain it to others.
For instance, a log-normal distribution IDENTICAL to the ones we’re talking about here could be created by plotting the birthdates of each precinct/ward captain using this bar chart distribution plotting method (except with bins 1-12). That data is obviously utterly meaningless, but the chart would tell the exact same story (at least as the honest Trump plots). Point being, WHAT is being plotted absolutely cannot be ignored. “Trust but verify” as someone famous once said, especially with pretty pictures.
Stepping down from my angry scientist soapbox (sorry), I now understand what is going on here, and the results are extremely compelling. I would like to know how many total data points there are, which I think would equal the total number of precincts/wards in each of the three cities. Curious if we’re talking tens or hundreds (probably not thousands) of individual election results. The more data points the stronger the evidence of fraud.