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What are the odds? All dumps favour Biden

If all mistakes favour one candidate they probably weren’t mistakes.

h/t David E.

A group of hard maths guys go through the election data with an algorithm looking for instances of unusually large sudden additions of votes in batches much faster than almost all the others, and far above the “normal” pace. “Odd” in this case means absurdly unusual — in Minnesota one dump at 5:30am was a net gain of 113,755 Biden votes at 19 standard deviations from normal or a probability of 1 in 1081. These are astronomical numbers.

This report is well worth scrolling through. Each state has a batch of graphs. The outliers are obvious without any statistics.

Note, these are not necessarily fake votes or illegitimate. They are flagging them for investigation. But they didn’t find any dumps for Trump.  Hm?

Fourteen states are reported, and it’s somewhat disturbing to see dumps in states that have been off the radar like Kentucky and Maine. There were so many dumps in Pennsylvania and Virginia they had to change their definitions.

Without the step jumps in vote counting, the end graph would have been a massive landslide victory for Donald Trump. In Florida after batch #50, almost all Bidens gains were in step jumps. Some 600,000 votes were added. Imagine if Trump won Florida  by 360k, but perhaps was one million votes ahead? In which case his 3% win would have been a 9% win.

Florida Voting, Dumps, Graph

Florida Voting Dumps and a close up of the “key” hours. Imagine the blue line without the step ups?

Try to imagine there is a legitimate explanation for all dumps going Bidens way. What kind of process could lead to these anomalies?

Try to imagine the New York Times discussing this study.

I note the John Droz (familiar name to climate skeptics) is on the list of authors. Thanks to them all.

2020 Presidential Election Startling Voting Spikes

Report: Statistical Analysis of State Vote Dumps in the 2020 Presidential Election

Eric Quinnell (Engineer); Stan Young (Statistician); Tony Cox (Statistician); Tom Davis (IT Expert); Ray Blehar (Government Analyst, ret’d); John Droz (Physicist); and Anonymous Expert

Executive Overview
A team of unpaid citizen volunteer mathematicians, scientists, IT veterans, and engineers collaborated in a statistical vote analyses of selected states in the 2020 Elections. The purpose of a statistical analysis is not to tell what happened (e.g., ballot stuffing, machine algorithm, etc.), but rather where (ideally by precinct) there were unusual results.

In this special report we are looking at what has been called vote “Dumps.” We are defining a Dump as being a 25,000+ vote differential between Presidential candidates, received/recorded at one time. We looked for such influxes for both candidates. The conclusion is that all we were able to find were net Biden Dumps (see next page, Table 1, where the states are listed alphabetically, and the dumps chronologically). Unless otherwise noted, all data on Table 1 are from Edison time-series analysis of rates of votes added.

Again, we cannot determine exactly what happened to cause these Dumps (e.g., ballot stuffing, something legitimate, etc.), but rather where (a State) and time(s) that these unusual results took place.

Note, these are not necessarily fake votes or illegitimate.

*A “Net Vote Dump” is defined as a 25,000+ vote differential between 2020 Presidential candidates, at one time. All were for Biden as we were not able to find any cases for Trump that met this criteria. (If any can be documented, we’d be glad to do an update and include them.)
**PA and VA are exceptions for the 25k differential we are using. For whatever reason (and unlike most other states) they have way too many over 25k. As a result, the PA threshold is 60k and VA is 100k.

The comment on Pennsylvania is telling:

Pennsylvania
Evidently Pennsylvania and Virginia were engaged in a contest to see which state could produce the most convoluted election data. After struggling to make heads or tails of both, we think it’s a draw. In the case of Pennsylvania, it’s impossible to provide meaningful graphs in our Report — as multiple speculative assumptions would have to be made. To give the reader a grasp of what we faced, below (Table 3) is a list of all of the large differentials (i.e., Biden minus Trump results at individual time stamps). A major problem is that there are multiple examples where someone “corrected” the data — by making huge subtractions. Whether these are justified or accurate is anyone’s guess. Rather than take on the impossible task of sorting this all out, we selected four time periods that we believe are representative of suspicious Biden minus Trump differentials (See Table 1). We leave the rest of the challenge to a masochistic reader to tackle. Feel free to share if you can make any sense of it!

The cynic in me wonders what the point the all the graphs will be and hopes it’s not just so the corrupt can plan their dumps better in future.

That’s up to We The People. Pray they prevail.

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