"It Defies Logic": Scientist Finds Telltale Signs Of Election Fraud After Analyzing Mail-In Ballot Data

A most interesting thread popped up on Twitter Sunday from a data scientist who wishes to remain anonymous, regarding mail-in ballot data which strongly suggests fraud occurred in the wee hours of election night, when several swing states inexplicably stopped reporting vote counts while President Trump maintained a healthy lead over Joe Biden.
Using time series data 'scraped' from the New York Times website, the data - comparing several states (swing and non-swing) - clearly illustrates what fraud does and does not look like, and how several anomalies in swing states left 'fingerprints of fraud' as Biden pulled ahead of President Trump.

Presented below via @APhilosophae:

https://twitter.com/_/status/1325592112428163072

https://twitter.com/_/status/1325592240194981888

https://twitter.com/_/status/1325592664520142849

https://twitter.com/_/status/1325592832489508864

This is based on their proprietary "Edison" data source which would ordinarily be impossible to access for people outside the press. The CSV is available here. And the script to generate it is here. I suggest that everyone back up both of these files, bc this is an extremely important data source, and we cant risk anyone taking it down.

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

One of the first things noticed while exploring the dataset is that there seems to be an obvious pattern in the ratio of new #Biden ballots to new #Trump ballots.

[link to www.zerohedge.com (secure)]