Skip to comments.Mathematical Analysis On Election Data With Videos and Comments Linked.
Posted on 12/19/2020 9:12:41 AM PST by Son House
At minimum, three Mathematicians separately have
researched the data. Linked here are videos and
comments. I have indexed some videos. You will also
find data sets and spreadsheets. Also contained in
the links are some linked directions to do data analysis.
Michigan: The Polynomic Sledgehammer (no wheel!); a minimum
of 287,980 stolen from Trump past midnight on November 4th.
Remember that giant spike!
Conclusion of Regression Analysis, The Polynomic ledgehammer
Dr. Shiva is vindicated.
The total sum of votes stolen from President Donald J.
Trump, by this algorithm, hitherto named the Polynomic
Sledgehammer, is: 287,980 votes; bear in mind that Trump
lost the state by 154,188 votes.
The data above, with in excess of 99% R^2 values for degree
ten (Decic Regression), with catastrophic failures on
degrees 12, in all cases, and often on degree 11, with
degree ten always having the highest R^2 value of all the
prior degrees, is proof of algorithmic manipulation of the
election results in the State of Michigan.
Spreadsheet links (yes they are safe, ignore the warning).
Michigan; The Polynomic Sledgehammer
Streamed live 12 hours ago
Mathmatician explains that a ratio transfer algorithm picks the county and a precinct that he can easily find in given set of data.
BIG EVIDENCE of External Control (via software) Capping the
Maximum possible Votes Cast in Trump Strong Counties
This is clearly seen in some of the small counties data that
almost always vote for heavily for President Trump.
This ‘Capping’, however, did NOT occur in many Biden
stronghold Counties such as Wayne County. Obviously, it
seems real proof of a large, coordinated VOTER FRAUD scheme.
The Ratio Transfers in PA and GA.
Herein this list are all the precincts in city of Atlanta Georgia involved in these ratio transfers:
Found 2 more proofs at this link and a comment on the
obvious progression, what I consider the underestimated magnitude.
“All the coders, hackers, IT professionals in my channel chat
understood everything and even simplified half of my scripts
and column formulas. I’m pretty sure they all know how to do
it faster than I can now.”
A minimum of 124,000 votes were stolen from Trump in four counties in PA.
A few noteworthy comments from that link;
a difference of 124,649 votes, that I claim hereby claim,
were stolen from President Donald J. Trump, in these four
counties alone of Allegheny, Chester, Montgomery and Philadelphia.
Furthermore, I do not claim, but I do suspect, based on
“Second Tensor Analysis,” (explained in the detailed report
below), that the entirety of the State of Pennsylvania was
seized by this algorithm, since the Second Tensor contained a “Wheel Number,”
...although let it be noted that the Republican counties of
Greene, Cambria and Washington, showed suspicious activity
of ratio transfers in a prior investigation.
Video: Ratio Transfers Proved; Entire Algorithm Reversed
“10: That the fraud is proven by the fact that all hijacked
precincts in their final states can be filled with the same
number of votes per precincts, and it equals the same flip
of trump to total (confirming a live algorithm was balancing
the zero point average from a blank template using equal
weight on each precinct).”
Here’s an index;
8:00m, 22:00m, 27:00, watch
for about 3 to 4 minutes to get the big ideas,
42:00m Summarizes how the algorithm works
66:00m Real Evidence about 6 to 8 minutes long
88:30m Reverse engineering the wheel
105:00m Well balanced wheel
106:00m More evidence of fraud as the wheel folds in like a fan
134:30m The tree re-balancing may be related to the roll back of votes counts seen
139:00m Summation formula of splitting the load between precincts
140:00 The wheel number
Video linked here: A index for this proof Minnesota 2% strategy;
1:45 “the third party votes were coming in at higher than 2%
so what they did is they knocked 645 votes off the third
party candidates which is roughly a 5% or 4.8% change” now I
don’t know what happened to those votes but I do know they
are no longer counted for the third party, and it like
they’re basically gone.”
3:15 “the vote total had gotten so fast, it went from 2.1 to
2.9% which is a huge jump, so what you’ll see is the cheating
algorithm essentially we hit 3% and it had a major
correction, brought it right back down to 2.1% again, and
what that did is they stole 13,500 votes from the third
party candidate and that dropped the percentage like they
stole 30%, and that almost a third of what was going to the
third party at that time, just gone.”
3:45 “their strategy here was to keep those votes,that go to
the third party at 2.1%”
7:45 “Because there are votes taken from all three
candidates it creates an air of mystery, and so it can’t be
proven either way and this is the smokescreen that they’re
running in order to not be easily detected.”
7:58 “the strategy that they went with is the third party
candidates votes were not allowed to get more that 2.1% and
votes were consistently stolen from the third party.”
Came across this quote too;
Salomon “I found a solution to an inverse floor function to a
tremendous set of data (the flagged data), a solution that
cannot exist for natural data. I re-balanced the wheel with
that solution. It’s Fraud.”
Spreadsheet linked here
that may help, if I don’t respond after this, either me or my computer crashed;
Video: 4th mathematician explains:
A key point is how unlikely it is for several districts under
investigation to get EXACTLY the same vote ratio
Video: Simulation, Fraction Magic: Integer Ratio Transfers
“Simulation of hypothesized Vote Transfer observations of election data.
Trimming only optimizes visual focus of the material, does not affect content.”
Video: Piton explains finding what he calls a Phantom voter that is shuffled where needed.
Real important after understanding high frequency stock trading and -14:00m
Updates on Voter Fraud in Pennsylvania
Timestamps easier in reverse starting total about 50 minutes
-21:25 results created with U-Voters and swap
-17:25 Re-explain U-Voter and Phantom Voter 5 ways to cheat
-15:15m Data Set for the whole country
-14:00 Why those updates occurred sending odds tables to the machine
-13:20 Reason why they had to stop the count during
election, they didn’t know where they were at with how many fillers they needed.
-13:10 It threw off all their probability tables
-11:30m because they bullied Trump supporters so much, they
couldn’t calibrate the odds properly
-8:28m They modify the voting record of people quickly
-8:13m There is a digital paper trail, they won’t release it
-6:60m Data set for the entire nation
Video: Recent Piton interview;
8:30m Piton explains when he started this
14:00m When he figured out what was happening, slight changes
15:50m I’ve identified ways, we won’t get into those
19:50m Real Example
23:00m Classification of voters represented by precinct
25:50 Then replicated in Pennsylvania
26:40m Finding 20 to 30 percent Phantom Voters Found 539 of 1000m didn’t exist
32:00m Addresses that aren’t there
“The number of Phantom Sleeper Voters is up to a minimum of
267,067 with only about 44 counties in PA complete. I will
pause to create the next set of age statistics as the
evidence is overwhelming they exist across every county that
I have examined in PA so far.”
More information tomorrow.
“Time to write up findings for Congressional Candidate that
had the election wrongfully taken from them. The Data is overwhelming.”
“Updated last night about AZ by Liz Harris MBA
regarding the 95K names I identified and sent her about
Phantom Sleeper Voters. Out of 2,000 knocks and 1,000
responses 539 were found to be ghosts. They didn’t exist”
Dec 10, 2020
“someone close to our @POTUS reach out to me last night to
discuss all of my findings. I spoke just over 22 minutes.
Same amount of time as testimony in AZ. I will be getting
them information to explain how it was perpetrated.”
“The scam is to send in a #phantomvoter to kill a real
persons vote and place their vote in it’s place. Then wipe
record clean of #PhantomSleeperVoters to cover tracks.
People give up looking because fraudulent vote transferred
to real person. When someone checks the file they think all
is ok and ignore #PhantomSleeperVoters because they wipe that one out.
Prove this via time stamps of record modifications. In #PA
Congressional Race over 40% of 520,000+ voter file or over
200,000 voting Files had records modified.”
Phantom Sleeper Voters
being injected into the count
“I have figured out an algorithm of how #PhantomSleeperVoters
are created in the data.
Based on results in AZ and soon... other States...
this will be proved out across US!”
Shiva explains it that decimal use denies “One Person, One Vote.”.
FIRST VICTORY in U.S. for #ElectionFraud lawsuit!
Federal Judge DENIES MA Sec. of State Galvin’s Motion to
Dismiss my Lawsuit that exposes computer algorithms were
used to steal votes in my U.S. Senate Election that
denies “One Person, One Vote.” Case is ON! Dr Shiva.
Video at link.
In 1st one, BIG VICTORY. Judge ordered MA Sec. of
State stop contacting Twitter & having me banned
for exposing MA uses algorithms & deletes Ballot Images.
In 2nd asking hand-count of paper ballots in my US Senate run.
Dr Shiva speech in 3 parts on steps of Supreme Court
Dec 12, 2020
Dr Shiva’s case;
Although SCOTUS minutes ago rejected TEXAS complaint, People
of America still have my lawsuit in MA, which remains the ONLY
complaint focusing on the REAL CRIME SCENE of #ElectionFraud:
COMPUTER ALGORITHMS that flip votes to deny you “ONE PERSON, ONE VOTE.”
Video: Interview, election part starts at 7:15m;
Dr Shiva Affirmed on the Dominion Algorithm Switch
Explaining the math from using this statement from the affidavit;
‘Each report of votes from a precinct contains a “timestamp”.’
The method “Intended Loser to Total Ratio”
3 results in a precinct, a loser, a winner, and 3pCandidate.
loser is given an exact number, always a constant (KEY)
-then the precinct has a leftover set to assign
winner is given a minimum number,
3pCandidate = 0
the leftover set is split between;
winner is tabulated to beat loser,
3pCandidate gets some of the leftover
so: winner > loser > 3pCandidate
remember, Intended Loser to Total Ratio?
That is what they find in concurrent timestamps, the ratio is transferring.
a simple example of something basic, but the big point is they have figured out the pattern and solve for an understanding of an algorithm or two, and what it was doing in the software depending on how the mathematicians solved it that I have been able to follow, there may be more mathematicians and probably is that are working out the data.
to put it in a very simple equation and extrapolate from there;
d = a + b + c
d is the summation of adding a, b and c together
but now before you add a, b and c, determine each as they accumulate different counts,
n, m, and l are the votes coming in being summed to the total
like ballots accumulate at a voting machine and now d becomes the outcome of the election
d = (a + l) + (b + m) + (c + n)
d = (a + l) * k))
the a accumulates as expected but * k means multiply it times a number
d = (9 + 1) * 1 = 10
d = (9 + 1) * 2 = 20
d = (9 + 1) * 3 = 20
so finally to tabulate 3 candidates and produce the outcome
d = (a + l) * i)) + (b + m) * j)) + (c + n) * k)) = result
result print line; a and b and c.
with the multiplier set to 1, each candidate gets the expected count as votes accumulate
but if you wanted to change the just change 1 to a decimal number near that,
say 1.3 or 0.7, then
d = (a + l) * k))
d = (9 votes + 1 vote) * 1.3 = 13
d = (9 votes + 1 vote) * 0.7 = 7
It is said that where there is smoke there is fire. But unless the responders can actually find the fire, smoke all there is.
d = (9 + 1) * 1 = 10
d = (9 + 1) * 2 = 20
d = (9 + 1) * 3 = 20
Voter fraud data set PING!
The judicial courts are in on the scam, he needs to take his case to the court of public opinion.
Very well done...thanks!
Is there a math major and/or programmer on site?
Excellent! Statistical PROOF OF VOTE MANIPULATION IN BIDEN’S FAVOR and PROOF that machine algorithms were STEALING VOTES FROM OM TRUMP and manipulating VOTE RATIOS.
This PROOF needs to be presented to INTELLIGENCE COMMITTEE.
Yes. What would you like to know?
Everything here makes beyond a reasonable doubt seem like a trivial standard.
But orange man bad
Sad but true. Only counts if:
1. Someone with authority gives a damn.
2. Must have actual PROOF.
This engineer can tell you that given enough degrees (exponents), he can fit a polynomial to almost anything.
Son House summary
“Is there a math major and/or programmer on site?
This engineer can tell you that given enough degrees (exponents), he can fit a polynomial to almost anything.”
This engineer too. Yup, just as you said.
Also, what is the interpretation of a 10 degree polynomial in the problem domain, or is there any such interpretation.
I couldn’t follow the poster wrote, I’ll admit that I didn’t try very hard. I can tell just by looking at the graphs I’ve seen on the net that the election was crooked. But, sad to say, I think the poster’s analysis is probably junk and therefore unhelpful. I’d like to see the opinion of someone with a stat degree.
Statistical Evidence of Dominion Election Fraud? Time to Audit the Machines.
Statistical analysis of past presidential races supports the
view that in 2020, in counties where Dominion Machines were
deployed, the voting outcomes were on average (nationwide)
1.5% higher for Joe Biden and 1.5% lower for Donald Trump
after adjusting for other demographic and past voting preferences.
FAQ page about this analysis.
More mathematics analysis;
December 20, 2020
“If we have 213.8 million registered voters in the US and
66.2% of all voters voted in the 2020 election, that equals
141.5 voters who voted in the 2020 election (Binney shows
140 million which is materially the same).
If President Trump won 74 million votes, then that leaves
only 67.5 million votes remaining for Biden. This means 13
million duplicate or made up ballots were created and counted for Biden!”
Video at link;
Phantom voters exposed: This is how Biden got 13 million extra votes;
16:25m Pennsylvania and High frequency trading-vote swap definition
22:00m 220k modifications to the voter files
22:45m Timestamps of digital transactions had to be coded
23:30m Figured out how the technology could be used
23:50m Host summarizes definition of vote swap
25:00m How can they figure that out?
26:50m Early voting
27:50m Updates were probability maps + Host summary
29:30m Paused the vote count
31:15m Reason why they paused the machines - min max range exceeded
37:15m This is all going to be proven
39:30m Explanation of 5 types Phantom voters
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