Joe Biden’s votes violate Benford’s Law (Mathematics)

Source of image: Twitter

As the vote counting for the 2020 Presidential Election continues, various facts suggest rampant frauds in Joe Biden’s votes. So does mathematics in terms of the votes from precincts.

Benford’s law or the first-digit law, is used to check if a set of numbers are naturally occurring or manually fabricated. It has been applied to detect the voting frauds in Iranian 2009 election and various other applications including forensic investigations.

This is what described by Wikipedia:

“Benford’s law, or the first-digit law, is an observation about the frequency distribution of leading digits in many real-life sets of numerical data. The law states that in many naturally occurring collections of numbers, the leading digit is likely to be small.

For example, in sets that obey the law, the number 1 appears as the leading significant digit about 30% of the time, while 9 appears as the leading significant digit less than 5% of the time. If the digits were distributed uniformly, they would each occur about 11.1% of the time. Benford’s law also makes predictions about the distribution of second digits, third digits, digit combinations, and so on.”

One of the examples is the population of the world, which are naturally occurring numbers.

Distribution of first-digit (in %) of population numbers in 237 countries in 2010.
Source: wikipedia.org

A number of people on the internet have checked the votes (precinct by precinct) of Joe Biden, Donald Trump as well as other candidates for their legitimacy in terms of the Benford’s Law.

According a Reddit user, r/dataisbeautiful’s calculation, the ‘normal’ distribution of first digits for the different candidates based on Benford’s law is illustrated below.

Source of image: https://bit.ly/3l7mUE5

Youtuber Nyar has shared the observations on a number of counties, concluding that Trump and others’ votes have natural distribution but not for Joe Biden’s.

In Fulton County, Georgia, which overlaps with the Atlantic metropolitan where Joe Biden is expected to win, all of the three candidates have normal distributions for their votes. (Joe Biden 72.6%, Donald Trump 26.2%, Jo Jorgensen 1.2%. Source: .theguardian.com)

Image from github.com/ (https://bit.ly/2GGTXjq)

In Miami-Dade County of Florida, which includes the Miami metropolitan where Joe Biden is expected to win, all candidates’ votes obey Benford’s Law. (Joe Biden 53.4%, Donald Trump 46.1%, Jo Jorgensen 0.3%. Source: theguardian.com)

Image from github.com/ (https://bit.ly/2GGTXjq)

However, in the Milwaukee County of Wisconsin, which is in one of the key swing states, Joe Biden’s votes violate Benford’s Law while other candidates’ don’t. (Joe Biden 69.4%, Donald Trump 29.4%, Jo Jorgensen 0.9%. Source: theguardian.com)

Image from github.com/ (https://bit.ly/2GGTXjq)

And in Chicago of Illinois, Joe Biden’s votes are abnormal.

Image from github.com/ (https://bit.ly/2GGTXjq)

So does that of Allegheny of Pennsylvania which includes Pittsburg. (Joe Biden 59.0%, Donald Trump 39.9%, Jo Jorgensen 1.2%. Source: theguardian.com)

It looks like maybe Biden had lost big cities like Chicago and Pittsburgh, which is why the fraudulent votes need to be brought in, which skew his curve away from a normal looking one.

For those who are interested to reproduce the analysis, you can follow the instructions here and give it a go.

Author: River|Himalaya Scholars

Proof-reader: XO酱

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cyclops
11 days ago

Actually, it doesn’t need much data, numbers on a newspaper would get this pattern. Check the explanation here https://youtu.be/vIsDjbhbADY

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cyclops
11 days ago

Actually, it doesn’t need much data, numbers on a newspaper would get this pattern.

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16 days ago

If I understand Benford’s Law correctly, its applicability to a set of numbers increases when the set encompasses a wide range of orders of magnitude. Without having a look at the raw data the graphs above represent I couldn’t tell you if they cover a wide range of orders of magnitude or not, but it would be my guess that most voting precincts produce similar numbers of votes. I’d guess most precincts produce roughly between 100 and 1000 votes, a difference of only one order of magnitude. Benford’s may not be the best tool for sussing out fraud in this… Read more »

cyclops
12 days ago

Yes, it might not be enough as direct evidence, in cases either fraudulance could produce the right pattern if the numbers were picked properly(eg. fulton county reportedly has other issues) or there would be special cases that are not fitting the law if the samples are not big enough. But this could be a guide to spot to the suspicious votes.

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16 days ago

What is the dataset represented by these graphs? So you have 2054 observations for Biden in Chicago and more than 600 of these start with the digit 3, but what is a single observation representing? Number of votes at a certain location, timeframe, what? If you can’t describe the dataset then I cannot take the charts seriously. It’s also inappropriate to apply Benford’s Law here. Data is likely to conform to Benford’s Law when the mean is close to an inflection point (10, 100, 1000, etc), and/or when the data reflects a population with exponential growth (like populations) The reason… Read more »

cyclops
12 days ago
Reply to  Cameron

It might not be enough, especially the data is not avaible. This Law has been applied for election forensics and it should be an indicator for the authority to find the suspicous votes. This law could be applied to state level that has big enough samples.

0
16 days ago

Like if they’d care wit whatever violates whatsoever… PFF

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17 days ago

Facebook, Instagram and WhatsApp is censoring this post and it is not possible to publish it even in Story. Try to share the link to this post and see the magic.

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T
17 days ago

Claims that the number set is too small are erroneous. Be Ford’s Law is used to detect tax evasion. The numbers of voters are in fact similar to those individuals paying tax. So the claim that the application of Be Ford’s Law to vote fraud cannot be applied is false.

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17 days ago

The problem here is that the TOTAL votes don’t match Benford’s law either. There is not enough random data for Benford to apply. Take Allegheny County. Apply the same logic to total votes and you see a huge spike in the ‘4’ column (so there are many districts with a total of 400-499 votes). In a fairly close race the winner is therefore likely to get a lot more figures in the ‘2’ column. You would EXPECT the winner to have a taller ‘2’ column than a ‘1’ column. If they DIDN’T it would look suspicious. The rules for Benford… Read more »

17 days ago

These types of distributions work on large, natural datasets, but not on small subsets or ones that are influenced by certain factors. For instance, if you look at number of registered Democrats in these specific locations, you might find a very similar ‘non Bedford’ distribution, if you look at specific counties that swung for Trump in the same manner as these swung for Biden, you may find ‘non Bedford’ distributions. The issue with distributions like this is that, while large datasets will generally follow these curves, you can almost always go into subsets and find wild swings in either direction.… Read more »

17 days ago
Reply to  dnick

They seem to be working just fine on all the other candidates. You have a hole in your logic the size of one of those vans marked Biden/Harris on the side that were spotted by witnesses unloading numerous cartons of emergency “ballots”

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18 days ago

So, Benfords law does not apply to this data set. I checked the chicago numbers that you can download from GitHub which they used. I made same graph as they did. But the number of votes in each precinct is tight, 460 +/- 150 1 stdev. Given Dems normally win around 80-90% of the votes in this area. It means Biden didn’t get many 100’s votes, while Trump did as 10-20% of of the the totals give lots of 100’s. I could not find the Milwaukee data, but 5 times less data, even less reliable.

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17 days ago
Reply to  Mackle

Your logic is flawed. It’s been many years since democrats won elections without cheating so you are making an assumption based on prior fraud and your assumption is not logical. Their methods of fraud may become more technically sophisticated as time marches on, but the fact that they are fraudsters hasn’t changed since they stuffed ballot boxes before the Civil War in efforts to make slavery legal in new states.

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18 days ago

I shared a link to this on Twitter. They not only banned me for 12 hours IMMEDIATELY, i.e. automatically, but the reason they gave was: “Violating our rules against posting or sharing privately produced/distributed intimate media of someone without their express consent. “

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18 days ago
Reply to  DoubtingRich

Same thing happened to me too!

0
18 days ago

Some objections say that the data must cross two orders of magnitude to be valid. Any comments on this?

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18 days ago
Reply to  Almiller

Then why do all Trump’s results fit Benford’s law? Why do all the results in counties which are less critical, or harder for Democrats to corrupt, fit Benford’s law? That is why you don’t just look at Biden’s data, but compare it to Trump’s. The calculation I saw (the website is suspiciously down at the moment) had the p value for Trump 3×10^22 higher than that for Biden’s data. It is hard to understand such numbers. That is 30,000 billion billion. If you count up by 750 every second, and you started at the beginning of the universe, you would… Read more »

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