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Scientist finds telltale signs of voter fraud after analyzing mail-in ballot data – Dateway

A very interesting thread popped up on Twitter Sunday from a data scientist who wishes to remain anonymous, regarding postal voting data that strongly suggests that fraud has taken place in the wee hours of election night, when several shifting states inexplicably stopped reporting the vote count while President Trump maintained a strong lead over Joe Biden.

Using time series data “ pulled ” from the New York Times website, the data – comparing multiple states (swing and non-swing) – clearly illustrates what fraud is done and does not looks like, and how several anomalies in swing states left ‘fraud fingerprints’ as Biden edged out President Trump.

Featured below via @Aphilosophae:

Continued…

This is based on their proprietary “Edison” data source which would normally be inaccessible to those outside the press. CSV is available here. And the script to generate it is here. I suggest everyone to save these two files, bc this is an extremely important data source, and we cannot risk anyone deleting it.

What we are looking at will be time series analysis and you will see that it is extremely difficult to create compelling synthetic time series data. By looking at the time series logs of the ballot counting process for the whole country, we can very easily spot the frauds.

One of the first things noticed when exploring the dataset is that there seems to be an obvious trend in the relationship between the new #Biden newsletters and the new #Trump newsletters.

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As we can see from this log chart, for most count progress updates we see an almost constant ratio of #Biden to #Trump. It’s such a regular model that we can actually fit a linear regression model to it with almost perfect precision, except for some outliers. How could this be possible? Is this a telltale sign of fraud? Surprisingly, as will be shown, the answer is no! This is in fact an expected behavior. As well, we can use this strange pattern in ballot counting to spot fraud!

Here is the same diagram for Florida. We see this linear model again.

And even (Texas)

And even (South Dakota)

And again throughout the country. What seems to be happening is that the dots on the straight line are actually mailed in the votes. The reason they’re so seamless regarding the ratio of #Biden vs #Trump votes is that they are randomly shuffled in the mail like a deck of cards. Since the ballots are randomly shuffled during transport, covering areas occupied by multiple demographic groups, we can expect that the ratio of #Biden mail-in ballots to #Trump mail-in ballots will remain relatively constant. over time and through the various report updates.

Lets dig a little deeper into this:

Here’s a graph of the same Florida voting data, but this time it’s the ratio of the #Biden to #Trump ballots, as a function of time. What we find is that the initial voting reports are very loud and “hit and miss”.

The initial report represents the vote in person. These voting reports exhibit such variation as in-person voting occurs in different geographies that have different political alignments. We can see this same noisy in-person voting pattern, followed by consistent reporting by mail in almost every case. What we see in almost every example across the country is that the ratio of Dem mailed ballots to Representatives is very constant over time, but with the Dem noticeable drift to a bit more. of representatives.

This slight drift of D-to-R mailings occurs over and over again, and is probably due to the fact that peripheral rural areas have more R votes. These peripheral areas take longer to send their ballots to polling centers.

Now we get into the really good stuff. When we see the postal ballot count where there are no relatively stable ratios of D and R ballots that drift slightly R, we have an anomaly! The anomalies themselves aren’t necessarily fraud, but they can help us spot fraud more easily.

Now let’s look at some anomalies:

This is the Wisconsin vote counting history log. Again, on the Y axis we have the ratio of D to R ballots in the reporting batch, and on the X axis we have the report time. Around 4 a.m. there, there is a marked change in the ratio of the D / R mail ballots.. From other articles in this thread, this should not happen. This is an anomaly, and although anomalies are not always fraud, they can often indicate fraud.

At 4 am, the D / R ratio was completely destabilized. This is because these ballots were not sampled from the actual Wisconsin electoral population, and they were not randomized in the mail sorting system along with the other ballots. They inherently have a signature D to R that is different from that of the rest of the ballots, possibly because additional ballots were added to the batch, either by back-dating, manufacturing ballots, or forging. software. This is somewhat analogous to carbon 14 dating, but for the authenticity of the voting batches.

Let’s look at another anomaly (Pennsylvania):

This is the story of the Pennsylvania vote count. For the first part of the counting process, we see the same pattern for mail ballots that we’ve seen in every other state across the country, which is a relatively stable D / R ratio that gradually drifts R as we go. as the number of ballots increases. But as the count continues, the D / R ratio in the mail ballots inexplicably begins to “increase”. Again, this should not happen, and it is observed almost nowhere else in the country, because all the ballots are randomly shuffled in the postal system and must be consistent during the count. The only exceptions to this are other suspicious states which also exhibit anomalies..

Again, it is the proof of the backdating of ballots, of the manufacture of falsified software.

Let’s look at another anomaly:

In georgia we see pretty much the same story as Pennsylvania: increasing fractions of D mail ballots over time, even though it defies logic and we don’t see this model anywhere else in the country.

In Michigan, we see a combination of Wisconsin weirdness, with GA / PA weirdness. We see both signs of rejection of contaminated ballots and voting ratios drifting into dems when they shouldn’t be.

Virginia:

Now, to be fair, VA is the only state in 50 that has anomalies but has yet to be charged with voter fraud. I think this is the exception that proves the rule. Yet to understand what is causing this abnormal change, but here no one accuses me of holding it back.

Lets conclude this: It looks like the Dems shot themselves in the foot before everyone else did mail-in ballots actually facilitating mail-order fraud.. Because all the ballots go through the postal system, they are shuffled like a deck of cards, so we would expect the return of the ballots to be extremely UNIFORM in terms of D vs R ratio, but drift slightly towards R over time bc some of them the ballots travel further. This model proves fraud and is a verifiable timestamp of when each fraudulent action occurred.



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