
Source: Joe Hoft
We reported already that 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.
The concerns with the unreasonable increase in ballots in Wisconsin led to one expert to share with us his analysis on Wisconsin voter data. The results of this expert’s Bedford analysis, a statistical technique which identifies outliers in data sets, showed that Biden’s numbers in Milwaukee made no sense and due to the many outliers indicate potential fraud:

Now additional analysis shows that similar patterns exist for Biden in both Chicago and Pittsburgh:
The additional analysis shows Biden’s results in Chicago indicate fraud. Notice how Biden’s numbers are way outside of expectations and yet Trump and other candidates look reasonable:

Honest mistakes in reporting would go both ways instead of just in favor of the Dem candidates and THAT occurred in multiple venues. Call me crazy, but I don’t believe in coincidences like that.
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It’s called the Biden Skew!
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So is the Trump legal team going to use this?
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Reblogged this on Wake Up To The Truth.
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Reblogged this on Wake Up To The Truth.
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Wow, Chicago! As a downstate resident, I’d love to see Illinois flip!
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Credibility would be helped if you spelled Pittsburgh correctly!
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Benford’s Law does not apply to precinct results, because precincts by design have a similar number of voters in each precinct. It’s the same reason that if you measure the heights of all your friends in inches, you’ll find that doesn’t follow Benford’s distribution. (And this is also why if you do a similar analysis, but red state counties that voted for Trump, you’ll find the Trump distribution looks a lot like the Biden distribution in Chicago). Here’s a detailed explanation: https://www.youtube.com/watch?v=etx0k1nLn78
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