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How The 2020 Election Was Stolen

How people who should know better abuse math to bolster the ‘election fraud’ lie

Imagine that you run a small deli. Over the years, you’ve noticed that there’s a rhythm to when you sell sandwiches during the week, with a peak generally landing about 1:30 p.m. or so and then fading over the next few hours.

Curious about whether you can precisely predict daily sales, allowing you to manage supplies and staffing, you decide you’re going to track sandwich sales for a week. The result looks like this.




You’re not a math whiz, so you pass the data to your cousin Fritz, who has a PhD. Your question to Fritz is simple: How many sandwiches should you expect to sell each hour of a weekday?

In short order, he tells you something unexpected. The data you gave him isn’t sandwich sales at all. Instead, it’s phony data, derived from an algorithm aimed at masking deli fraud. And he can prove it.

See, if you take the sales from two days — say, Monday and Tuesday — and average the values, you can then create a sixth-order polynomial that describes the hourly pattern. Fritz’s PhD allows him to do the math himself, he assures you, but he passes along a formula that he derived from Excel. There it is: the precise formula for determining how many sandwiches (the y value) you will sell each hour (the x value). That’s math, hard at work, way beyond your ken — but precise.




But wait! If you take that same formula and compare it to the sales each day of the week, something alarming happens. The formula predicts the number of sandwiches being sold very well. Suspiciously well. If you look at the R-value of the correlation between the sales each hour and compare it to the formula, you get numbers that are very close to 1, meaning it’s a perfect correlation. And in a human-based system like sandwich sales, that shouldn’t happen!

Below, we used the average to do the R-value calculation, but you get the point. For each day, the predicated sales — here, the average — is extremely close to perfectly correlated to the actual sales. Ergo: This could be a function only of a computer-based effort to forge sales data.




You find this surprising for quite a few reasons. The first is that you tallied the sales yourself, so you know they’re correct. The second is that, even if Fritz were right that the numbers were artificial, why does he assume there’s some deli-fraud algorithm out there that’s responsible? The third is that, even without a PhD, you see a problem with Fritz’s analysis. He’s comparing an average derived from two of the values with all five of the values. Doesn’t it seem obvious that the result would be a strong correlation?

The answer, of course, is yes. Being surprised that sandwich sales over the course of the day is correlated to an average of the number of sandwiches sold over the course of two days is like being surprised that a coin comes up heads about half the time you flip it.

Or, more to the point, like being surprised that an estimate of voter turnout based on four counties in Michigan correlates strongly to voter turnout in nine counties in Michigan — including the four used to generate the “sixth-degree polynomial” (that complicated formula) in the first place.

This, however, is what the analysis of Douglas Frank, PhD, offers. Frank’s analysis of voter data in Michigan has led him to determine with seeming authority that the election results in that state were rigged, tailored to match the precise formula he himself derived from the state’s results. Claims like Frank’s analysis of Michigan have earned him the attention of MyPillow chief executive Mike Lindell, whose efforts to prove that voter fraud occurred in 2020 has led him to elevate all sorts of unfounded allegations about last year’s presidential election. Frank’s analysis has convinced others, too, with the conservative polling firm Rasmussen Reports elevating a write-up of his allegations over the weekend.





Rasmussen highlighted a different part of Frank’s assessment, the idea that about 66,000 Michigan voters cast ballots in last year’s election who weren’t in voter rolls in October. As The Washington Post’s Lenny Bronner quickly pointed out, Michigan has same-day voter registration, so those 66,000 voters are almost certainly just people who actually weren’t registered in October but who voted anyway.

The firm, which consistently showed more favorable approval data for Donald Trump over the course of his presidency than other pollsters, has repeatedly elevated dubious and unfounded fraud claims over the past few months. That’s aligned with a broader shift in its public-facing presence to be more aggressive toward critics from the mainstream media. (Last year, it accused me of “republishing a defamatory falsehood [and] committing fraud” for pointing out that its 2018 general-election polling showed Republicans with a one-point lead over the Democrats in an election where Democrats won more votes in House races national by a nearly 10-point margin.) Responding to Bronner’s tweet, Rasmussen offered the equivalent of a “just asking questions” shrug.

It should know better than to take Frank’s analysis at face value. This is a polling firm, after all, a company whose business is statistical analysis. Yet, there it was, sharing Frank’s claims uncritically.

Frank has been working with an attorney named Matthew DePerno, who has been sharing graphs from Frank’s presentation on Twitter with a bit of colorful commentary.





So what do those graphs show? What our third sandwich chart shows: that a prediction of how many votes would be cast in a Michigan county by age derived from the number of votes cast in a Michigan county by age correlates with the number of votes cast in a Michigan county by age. Frank does a lot of hand-waving on the side, like that discrepancy between the October voter roll and votes cast and by including comparisons of Census Bureau population estimates — which appear to be five-year averages of the population from 2015 to 2019 — are lower than the number of registered voters in some places. (Frank does point out that this could be a function of outdated voter rolls, but he doesn’t dwell on it.)

The heart of his analysis, though, is that R-value correlation between his predicted turnout and the actual turnout. How did he generate his prediction?

“What I actually did is I averaged four counties, the four largest counties, and used that key to predict all nine,” he explains. A few seconds later, he marvels that “the accuracy of my prediction is just ridiculously good. It shouldn’t be that good.”

Well, it should, because you are predicting data based on the data itself. If it weren’t a really close correlation, that’s when things would get funky.

Incidentally, that Frank is using a “sixth-order polynomial” doesn’t mean he’s doing some incredibly complicated calculation. It just means that he’s trying to fit his prediction as closely as possible to the existing data, thereby increasing the correlations.[/I]

OAN's math wiz turned out to be a convicted felon who makes his living assembling children's swing sets.

I think he works with the ditz in the OP as well.

 
Says the numpty that fails to put spaces after full stops and a space between "message" and "board".

I'm sorry that I'm not clued-up on internet pop culture abbreviations like BDS.
Really? The Grammar police? I've never known the grammar police to have anything worthwhile to say. Take for instance---messageboard. I see that this is a internet web message board and sure enough the web address that we all use to find this place is written out as www.usMESSAGEBOARD.com. with GULP!! no space between the words.
 
Alabama: was printed in bold letters in the JW watch article, right next to the first listing, Lowndes County (130%), just as I printed it under the link.

You had no need of a search.

Regardless of the reason for the registration roll exceeding the eligible voter population, the opportunity for fraud existed.

Your link is to a site that denies reading without first disabling ad-blockers or signing up, both of which I refuse to do.

Your link also says Ten Alabama counties...

Judicial Watch lists 25:
The potential for fraud always exists. That doesn't translate to fraud occurred.

Meanwhile, your guy claims voter rolls were hacked to inflate them. Where's the proof of that?
 
Of course the voter rolls were not up to date. Dead people and voters that moved did have ballots cast for them in the election.

He didn't claim that voter rolls were changed by the county precinct officials. He claimed that the voter databases were hacked and manipulated (before the election) to add fabricated phantom voters that did not exist so that during the election, if the results were not going the way the hackers wanted, they could add the phantom ballots to the tally (without actually scanning a real ballot) to maintain the lead in favor of their desired winner. They just had to be careful not to add so many as to exceed the number of age-eligible voters in the precinct they were hacking. That may explain their use of census data. If extra votes were not needed, they were not used.


Not so. In the 2020 election, this only had to occur in the swing states. You know, the ones that all stopped counting in the middle of the night because Trump was getting so many votes he was overwhelming their fraud system. That's when vote counts were actually taken from Trump and given to Biden. That's when a massive dump of votes occurred in one precinct where there were not enough scanning machines to have actually processed as many votes as were dumped in for Biden.


Executive Summary

In the early hours of November 4th, 2020, Democratic candidate Joe Biden received several major “vote spikes” that substantially — and decisively — improved his electoral position in Michigan, Wisconsin, and Georgia. Much skepticism and uncertainty surrounds these “vote spikes.” Critics point to suspicious vote counting practices, extreme differences between the two major candidates’ vote counts, and the timing of the vote updates, among other factors, to cast doubt on the legitimacy of some of these spikes. While data analysis cannot on its own demonstrate fraud or systemic issues, it can point us to statistically anomalous cases that invite further scrutiny.

This is one such case: Our analysis finds that a few key vote updates in competitive states were unusually large in size and had an unusually high Biden-to-Trump ratio. We demonstrate the results differ enough from expected results to be cause for concern.

With this report, we rely only on publicly available data from the New York Times to identify and analyze statistical anomalies in key states. Looking at 8,954 individual vote updates (differences in vote totals for each candidate between successive changes to the running vote totals, colloquially also referred to as “dumps” or “batches”), we discover a remarkably consistent mathematical property: there is a clear inverse relationship between difference in candidates’ vote counts and and the ratio of the vote counts. (In other words, it's not surprising to see vote updates with large margins, and it's not surprising to see vote updates with very large ratios of support between the candidates, but it is surprising to see vote updates which are both).

The significance of this property will be further explained in later sections of this report. Nearly every vote update, across states of all sizes and political leanings follow this statistical pattern. A very small number, however, are especially aberrant. Of the seven vote updates which follow the pattern the least, four individual vote updates — two in Michigan, one in Wisconsin, and one in Georgia — were particularly anomalous and influential with respect to this property and all occurred within the same five hour window.

In particular, we are able to quantify the extent of compliance with this property and discover that, of the 8,954 vote updates used in the analysis, these four decisive updates were the 1st, 2nd, 4th, and 7th most anomalous updates in the entire data set. Not only does each of these vote updates not follow the generally observed pattern, but the anomalous behavior of these updates is particularly extreme. That is, these vote updates are outliers of the outliers.

The four vote updates in question are:

  1. An update in Michigan listed as of 6:31AM Eastern Time on November 4th, 2020, which shows 141,258 votes for Joe Biden and 5,968 votes for Donald Trump
  2. An update in Wisconsin listed as 3:42AM Central Time on November 4th, 2020, which shows 143,379 votes for Joe Biden and 25,163 votes for Donald Trump
  3. A vote update in Georgia listed at 1:34AM Eastern Time on November 4th, 2020, which shows 136,155 votes for Joe Biden and 29,115 votes for Donald Trump
  4. An update in Michigan listed as of 3:50AM Eastern Time on November 4th, 2020, which shows 54,497 votes for Joe Biden and 4,718 votes for Donald Trump
This report predicts what these vote updates would have looked like, had they followed the same pattern as the vast majority of the 8,950 others. We find that the extents of the respective anomalies here are more than the margin of victory in all three states — Michigan, Wisconsin, and Georgia — which collectively represent forty-two electoral votes.

Extensive mathematical detail is provided and the data and the code (for the data-curation, data transformation, plotting, and modeling) are all attached in the appendix to this document[1].

Background

Late on Election Night 2020, President Donald J. Trump had a lead of around 100,000 votes in Wisconsin, a lead of around 300,000 votes in Michigan, and a lead of around 700,000 votes in Pennsylvania. Back-of-the-envelope calculations showed that in order to overtake President Trump, Joe Biden would have to substantially improve his performance in the remaining precincts — many of which were in heavily blue areas like Detroit, Milwaukee, and Philadelphia.

On Election Night, conflicting news reports came in that various precincts were stopping their count for the evening, sending election officials home, or re-starting their counts. There remains a large amount of confusion to this day about the extent to which various precincts stopped counting, as well as the extent to which any state election laws or rules were broken by sending election officials home prematurely. Whatever the case is, various precincts in Wisconsin, Michigan, and Pennsylvania continued to report numbers throughout the night.

By the early hours of the following morning, Wisconsin had flipped blue, as did Michigan soon after. A few days later, Georgia and Pennsylvania followed suit. Given the uncertain context, many American observers and commentators were immediately uncomfortable or skeptical of these trends.

For context, using publicly available data from the New York Times, here is a visualization of the number of votes by candidate in Michigan from the beginning of election night to 7pm Eastern Standard Time (EST) on November 4th, 2020:


Fig. 1. X-axis is the Month-Year Hour of the time, Y-axis is the number of votes as of that time, expressed in millions of votes. The red series is the running number of votes for Donald Trump, and the blue series the running number of votes for Joe Biden.

As this graph shows, Joe Biden overtook President Trump’s lead through a small number of vote updates which broke overwhelmingly for Biden in Michigan in the early hours of the morning of November 4th.

The situation in Wisconsin is even more stark: a single update to the vote count brought Biden from trailing by over 100,000 votes into the lead. Here is the comparable graph, over the same time range, for Wisconsin, with the x-axis (time) expressed in Central Standard Time (CST):


Fig. 2. X-axis is the Month-Year Hour of the time, Y-axis is the number of votes as of that time, expressed in millions of votes. The red series is the running number of votes for Donald Trump, and the blue series the running number of votes for Joe Biden.

Various versions of these graphs spurred online discourse. While some commentators provided relatively partisan analysis, others merely expressed surprise at the near-vertical leaps in some of these vote updates. Is it likely this phenomenon would arise organically? In an attempt to address this question, this report assesses how extreme and unusual these spikes are with respect to both other vote updates in the states of Michigan, Wisconsin, and Georgia, as well as those around the nation.

Through several investigative mechanisms, we find these four vote updates to be extraordinarily anomalous. While these alone do not prove the existence of fraud or systemic issue, it invites further scrutiny.

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Quantifying the Extremity

Having demonstrated visually how anomalous the four key vote updates are, we can now proceed to attempt to quantify how unusual it is that these three points exist at once and that two of them are from the same state.

The below graph has two particularly interesting visual properties:

  1. The graph is presented two-dimensionally, but it’s really three-dimensional. It’s visibly much denser in the center, has what appear to be something like two normal distributions, and as you move farther from the origin along a positive-sloping line which runs through the origin, the lower the density you can expect.
  2. The outer “edges” of the graph, in the top-right and bottom-left quadrants, closely resemble the shape of the line y = 1 / x.
We similarly expect points to be in both the top-right and bottom-left quadrants, and between an outer line which has the shape of y = 1 / x and the origin. Since these values will thus mostly be either both negative or both positive, we can see that multiplying each point’s x-coordinate with its y-coordinate is a useful way of assessing the extent to which it follows this sort of distribution. Since there are more points near the origin than there are on the visible “boundary lines” (i.e. the sequences of points on the outer edges in the first and third quadrants which visibly form these lines which look like a graph, if perhaps scaled, of y = 1/x).

We thus, for each (again, both standardized by state) coordinate pair of Biden-Trump margin and the log-ratio of Biden to Trump votes, can multiply these values and examine the distribution of the resulting products. Here, the larger a value is in magnitude, the less it follows the non-co-extremity. Plotting these products gives us:


Fig. 11. Histogram of products of x and y values for each coordinate pair in Fig. 10

As we can see, the values are overwhelmingly concentrated near the median, and the graph is profoundly right-skewed — otherwise, the x-axis would not need to stretch all the way to 80. All but 60 out of 8,954 unique updates have values less than 10, and all but 10 have values less than 20. In other words, an overwhelming share of updates seem to track this rule pretty closely, but a small number of updates are truly extreme outliers.

A quick dive into these ten points reveals data which, by this point in the report, will be very familiar to the reader:


As we can see, four of the seven most anomalous vote updates — which is to say, updates in which the margin and ratio are co-extreme — are in election-critical states and occurred during the same five hour period where the circumstances on the ground were (and remain) contested and highly suspicious.

It is worth noting here that roughly 15% of the vote updates in the data set of 8,954 were from these three states. If we assumed it equally likely that any particular state should end up at any of these extreme points, there would be about a 1.2% chance that three states are represented in three out of the top four or four out of the top seven spots, and about a 0.99% chance that these three states would occupy five out of the top seven spots. It is thus very surprising to see the states in question be so disproportionately represented in the top 0.11% of the distribution of co-extremity[17].

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Conclusion

This report studies 8,954 individual updates to the vote totals in all 50 states and finds that four individual updates — two of which were widely noticed on the internet, including by the President — are profoundly anomalous; they deviate from a pattern which is otherwise found in the vast majority of the remaining 8,950 vote updates. The findings presented by this report [28]suggest that four vote count updates — which collectively were decisive in Michigan, Wisconsin, and Georgia, and thus decisive of a critical forty-two electoral votes — are especially anomalous and merit further investigation.

In particular, the finding that the broader data follows general patterns and our ability to measure just how much any individual vote update does — or doesn’t — follow this pattern allows us to make concrete claims about both how extreme any given vote update is and about what any particular vote update might have looked like, had it been less extreme one one axis or another.

We further find that if these updates were only more extreme than 99% of all updates nationally in terms of their deviation from this generally-observed pattern, that, holding all else equal, Joe Biden may very well have lost the states of Michigan, Wisconsin, and Georgia, and that he would have 42 fewer Electoral votes — putting Biden below the number required to win the Presidency. Either way, it is indisputable that his margin of victory in these three states relies on four most anomalous vote updates identified by the metric developed in this report.

We once again note that this analysis is largely restricted to four individual vote updates out of a sample of nearly 9,000. This report by no means suggests stopping investigations in Michigan, Wisconsin, Pennsylvania, Georgia, or elsewhere; it is merely that these four key ballot updates are both profoundly anomalous with respect to a metric which removes any component of different states having different partisan leanings or a different number of voters. Furthermore, this analysis does not require that we regard the final vote totals in any of these states (or counties thereof) as suspicious, nor, critically, does it require that we accept that the observed data should follow any particular distribution a priori. We merely show that the data, adjusted appropriately to remove differences in size and political leaning between states, does follow a certain pattern, and that four key vote updates deviate profoundly from that pattern.

It is our belief that the extraordinarily anomalous nature of the studied vote updates here, combined with the staggering political implications, demands immediate and thorough investigation.



Correction: a previous version of this post calculated the probability of vote updates Georgia, Wisconsin, and Michigan constituting five of the ten most co-extreme vote updates as 0.0037%. The actual value is closer to 0.99%. The authors apologize for the error and the post has been corrected to reflect this.

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"He claimed that the voter databases were hacked and manipulated (before the election) to add fabricated phantom voters that did not exist so that during the election"

So prove it ... prove every single counties' database was hacked. That's over 3,000 databases....
 
"He claimed that the voter databases were hacked and manipulated (before the election) to add fabricated phantom voters that did not exist so that during the election"

So prove it ... prove every single counties' database was hacked. That's over 3,000 databases....
You don't read well, troll. I already stated that this kind of shit happening in the five swing states was all that was required to give Biden the "win". It's quite obvious that it didn't happen in the states that Trump won.

Here's a county map:
1628874357949.png


Trump won all of the red counties. Biden won 477 counties, while Trump won 2,497 counties.

Here's a link with a map showing states won by each:

Down ballot races were not a concern to the hackers. Only the POTUS race. Duh!
Total bullshit.

Take it to court so we can all get a good laugh at it.

PS: Any word on why the supposedly rigged Wisconsin election sent more R's to the House than D's? No? Carry on.
As I said in a previous reply to this drivel, hackers were not interested in down ballot races.

Also, there were many paper ballots cast with no down ballot voting....just votes for Biden.


DUH!

Read about Wisconsin:

• There were more than 60,000 ballots where only Biden was selected, but no down-ballot Democrats were selected. (A similar oddity occurred in other swing states.) While it is true that more voters tend to cast ballots in the presidential race, Trump had less than a thousand of these types of ballots. Given that Trump has many supporters who will vote for him, but not for anyone else, even other Republican candidates, this is difficult to believe.
 
You don't read well, troll. I already stated that this kind of shit happening in the five swing states was all that was required to give Biden the "win". It's quite obvious that it didn't happen in the states that Trump won.

Here's a county map:
View attachment 525163

Trump won all of the red counties. Biden won 477 counties, while Trump won 2,497 counties.

Here's a link with a map showing states won by each:



As I said in a previous reply to this drivel, hackers were not interested in down ballot races.

Also, there were many paper ballots cast with no down ballot voting....just votes for Biden.


DUH!

Read about Wisconsin:

• There were more than 60,000 ballots where only Biden was selected, but no down-ballot Democrats were selected. (A similar oddity occurred in other swing states.) While it is true that more voters tend to cast ballots in the presidential race, Trump had less than a thousand of these types of ballots. Given that Trump has many supporters who will vote for him, but not for anyone else, even other Republican candidates, this is difficult to believe.
"I already stated that this kind of shit happening in the five swing states was all that was required to give Biden the "win"."

Who cares what you say? Your boy claimed EVERY county was hacked.

Prove it.....
 
"I already stated that this kind of shit happening in the five swing states was all that was required to give Biden the "win"."

Who cares what you say? Your boy claimed EVERY county was hacked.

Prove it.....
I'm not obligated to prove it, certainly not based on the orders of an idiot like you. The hacking of the election has already been proved. You're just too dumb to understand that fact.
 
Down ballot races were not a concern to the hackers. Only the POTUS race. Duh!

That's almost as idiotic as the whole "the election was stolen" comedy show you've guys have put on.

Strange the same thing happened in Georgia with and there was a 50/50 split in MI....

Were all these done by the same hackers?
 
I'm not obligated to prove it, certainly not based on the orders of an idiot like you. The hacking of the election has already been proved. You're just too dumb to understand that fact.
You would if you could. You're not because you can't. You fool no one and at the same time, you just exposed what a fraud Frank is.
 
You don't read well, troll. I already stated that this kind of shit happening in the five swing states was all that was required to give Biden the "win". It's quite obvious that it didn't happen in the states that Trump won.

Here's a county map:
View attachment 525163

Trump won all of the red counties. Biden won 477 counties, while Trump won 2,497 counties.

Here's a link with a map showing states won by each:



As I said in a previous reply to this drivel, hackers were not interested in down ballot races.

Also, there were many paper ballots cast with no down ballot voting....just votes for Biden.


DUH!

Read about Wisconsin:

• There were more than 60,000 ballots where only Biden was selected, but no down-ballot Democrats were selected. (A similar oddity occurred in other swing states.) While it is true that more voters tend to cast ballots in the presidential race, Trump had less than a thousand of these types of ballots. Given that Trump has many supporters who will vote for him, but not for anyone else, even other Republican candidates, this is difficult to believe.
In your last comedic post, you said the "hackers" weren't concerned with down ballot races. Now you're saying there were fraudulent paper ballots.

Why would someone have to do paper ballots if they could just change the results?

Really...you should sell this story to a publisher....few have your imagination.

PS: Any arrests yet?
 
Don't bother dismissing the source, just watch the video. It's from Rumble.


Here's the real reason and it's not called stealing.
Trump proved to be an idiot and a non deliverer. Joe cleverly manipulated the silent majority by talking to them and their base quietly. He didn't need crowds at rallies to prove anything.
It was disgruntled republicans who turned against trump and voted dems. The stats are there to prove that.

There is No evidence of fraud whatsoever and you all know it. Nothing.
If Joe learnt anything in that forty years in congress, it was to read the mind if the electorate. He very cleverly orchestrated them to change and they did.
Yet all you psychiatrists tell me has senile. If that's senile, give me more of them
 
Don't bother dismissing the source, just watch the video. It's from Rumble.


Here's the real reason and it's not called stealing.
Trump proved to be an idiot and a non deliverer. Joe cleverly manipulated the silent majority by talking to them and their base quietly. He didn't need crowds at rallies to prove anything.
It was disgruntled republicans who turned against trump and voted dems. The stats are there to prove that.

There is No evidence of fraud whatsoever and you all know it. Nothing.
If Joe learnt anything in that forty years in congress, it was to read the mind if the electorate. He very cleverly orchestrated them to change and they did.
Yet all you psychiatrists tell me has senile. If that's senile, give me more of them
 
Here's the real reason and it's not called stealing.
Trump proved to be an idiot and a non deliverer. Joe cleverly manipulated the silent majority by talking to them and their base quietly. He didn't need crowds at rallies to prove anything.
It was disgruntled republicans who turned against trump and voted dems. The stats are there to prove that.

There is No evidence of fraud whatsoever and you all know it. Nothing.
If Joe learnt anything in that forty years in congress, it was to read the mind if the electorate. He very cleverly orchestrated them to change and they did.
Yet all you psychiatrists tell me has senile. If that's senile, give me more of them
:laughing0301:
 

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