Audit Statistical Technique Known as ‘Benford Analysis’ Points to Milwaukee Precincts as Central Point to Uncover Fraud
By Joe Hoft | Published November 7, 2020 at 7:00am
By using the audit statistical technique known as ‘Benford Analysis’ the precincts in Milwaukee are where the focus of any fraud audit in Wisconsin should take place.
In Wisconsin on the night of the election, President Trump was winning early into the morning. However, when Americans woke up on Wednesday Joe Biden had somehow taken the lead in Wisconsin after a vote dump of 100,000 votes appeared overnight.
Everyone in the US knew Wisconsin had been stolen and the votes for Biden all appeared at once in the middle of the night:
The concerns with the unreasonable increase in ballots in Wisconsin led one expert to share with us his analysis on Wisconsin voter data as it currently stands. Our expert who remains anonymous shared with us his analysis using the audit statistical technique known as Benford Analysis. This technique identifies outliers in data sets. Our expert shared:
I saw that some people had the idea of analyzing vote totals in context of Benford’s Law, so I ran a first-digit analysis on precinct-level vote numbers coming out of Wisconsin, using data from the 15 largest counties (skipping 2 which had unworkable data).
Of the 4 counties, 802 aggregated precincts comprising the Milwaukee Metropolitan Area, we get a significant deviation from the expected using Biden’s vote totals, and a p-value of 0.00002 (0.002% probability of a result at least as extreme as this one). Clearly, it does not follow the expected pattern. Trump’s vote totals are much more consistent, with P = 0.87. [The Biden data makes no sense in Milwaukee.]
Aggregating the other 11 largest counties, 1040 precincts, both appear normal for both candidates:
