Exposing the 2016 Popular Vote Myth

Exposing the 2016 Popular Vote Myth

Richard Charnin

April 5, 2018

The myth that Clinton won the popular vote by nearly 3 million is parroted daily by pundits, even Trump supporters. Clinton won a fraudulent recorded popular vote, but Trump won the True Vote. It’s 2018 and the pundits still fail to recognize the historical fact that the recorded vote is never the same as the True Vote.  It’s past time for a great awakening.

Trump won the estimated True Vote by 50.5-43.4%, a 9.7 million vote margin. We estimate the True Vote based on the following simple models:

• 1 Adjustments to the recorded vote: illegal votes , disenfranchised voters, voting machine flips 
• 2 Race: Census breakdown and shares of white and non-white voters
• 3 Returning 2012 voters and 2016 vote shares
• 4 Party-ID: Gallup voter survey and vote shares
• 5 When Decided: before and after Sept. 1

Given Model 1 adjustments to the recorded vote, we calculate an estimated True Vote. In models 2,3,4,5 we estimate vote shares required to match the True Vote.

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1672204415 https://www.theepochtimes.com/voting-machines-in-16-states-tied-to-george-soros-ally_2176907.html http://www.cnn.com/election/results/exit-polls/national/president

https://www.investors.com/politics/editorials/trump-is-right-millions-of-illegals-probably-did-vote-in-2016/

Input

Estimate

Clinton

Trump

Other

Illegal	3.0 mil	85%	10%	5%
Disenfranchise	4.0 mil	85%	10%	5%
Machine Flip	7.0 mil	0%	90%	10%

1 Adjust	Total	Clinton	Trump	Other	Margin
Recorded	136.22	65.72	62.89	7.61	2.83
		48.25%	46.17%	5.59%	2.08%
Illegal	-3.0	-2.55	-0.30	-0.15	-2.25
Disenfran	4.0	3.40	0.40	0.20	3.00
Vote Flip	0.0	-7.00	6.30	0.70	-13.30
Total Vote	137.22	59.57	69.29	8.36	9.72
True Vote		43.41%	50.50%	6.09%	7.08%

2 Census	Pct	Clinton	Trump	Other
white (adj.)	73.30%	32.4%	61.14%	6.5%
Black	12.45%	84%	13%	3%
Latino	9.22%	66%	28%	6%
Asian	3.67%	65%	27%	8%
Other	1.36%	56%	36%	8%
True Vote	100.00%	43.41%	50.50%	6.09%
Recorded	100%	48.25%	46.17%	5.59%
3 Party-ID	Gallup Pct	Clinton	Trump	Other
Dem	31.0%	88.0%	10.0%	2.0%
Rep	28.0%	5.0%	92.0%	3.0%
Ind	41.0%	36.0%	53.0%	11.0%
True Vote	100.0%	43.44%	50.59%	5.97%
Votes	137.22	59.61	69.42	8.19
4 Returning 2012 voters	Mix	Clinton	Trump	Other
Obama	41.33%	85%	10%	5%
Romney	40.80%	5%	92%	3%
Other	1.54%	35%	40%	25%
DNV (new)	16.32%	35%	51%	14%
True Vote	100.0%	43.43%	50.61%	5.96%
Votes	137.22	59.59	69.45	8.18

5 When Decided	Pct	Clinton	Trump	Other
Before Sept 1	60.0%	48%	48%	4.0%
After Sept 1	40.0%	37%	54%	9.2%
True Vote		43.41%	50.50%	6.09%

Sensitivity Analysis

Trump
% Whites	59.0%	60.0%	61.0%	62.0%	63.0%
% Blacks			Trump %
16%	49.28%	50.01%	50.75%	51.48%	52.21%
15%	49.15%	49.89%	50.62%	51.35%	52.09%
14%	49.03%	49.76%	50.50%	51.23%	51.96%
13%	48.91%	49.64%	50.37%	51.10%	51.84%
12%	48.78%	49.51%	50.25%	50.98%	51.71%
			Clinton
16%	44.63%	43.90%	43.16%	42.43%	41.70%
15%	44.75%	44.02%	43.29%	42.56%	41.82%
14%	44.88%	44.15%	43.41%	42.68%	41.95%
13%	45.00%	44.27%	43.54%	42.80%	42.07%
12%	45.13%	44.39%	43.66%	42.93%	42.20%
			Share Margin
16%	4.65%	6.12%	7.58%	9.05%	10.51%
15%	4.40%	5.87%	7.33%	8.80%	10.26%
14%	4.15%	5.62%	7.08%	8.55%	10.02%
13%	3.90%	5.37%	6.83%	8.30%	9.77%
12%	3.65%	5.12%	6.59%	8.05%	9.52%
			Vote Margin
16%	6.38	8.39	10.40	12.41	14.43
15%	6.04	8.05	10.06	12.07	14.08
14%	5.70	7.71	9.72	11.73	13.74
13%	5.36	7.37	9.38	11.39	13.40
12%	5.01	7.03	9.04	11.05	13.06

My Books

Trump Won the True Vote

77 Billion to One: 2016 Election Fraud

Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll

Reclaiming Science: The JFK Conspiracy

LINKS TO  POSTS

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Generic vote forecast model vs RCP average (10-29)

Analysis of inflated Democratic generic polls indicates Republicans will win the House

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Florida Governor Polling Analysis

Trump has a higher approval rating than MSM polls

Rasmussen vs. WaPo: Trump approval

 

 

2016 Election: illegal voters, uncounted votes, machine vote flipping

Richard Charnin
Updated Sept. 19, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Clinton won the recorded vote by 2.8 million. But the recorded vote is never equal to the True Vote due to election fraud.

There is evidence that millions of illegals probably voted in 2016. View this 1988-2016 trend analysis of Hispanic voter registration and turnout.

According to Greg Palast, least one million Democratic minority voters were disenfranchised via Crosscheckwhich eliminated voters with duplicate names from voter rolls. He claims that 7 million minority voters were disenfranchised.

There is evidence that  George Soros , a Clinton backer,  controls voting machines in 16 states.  Election analyst Bev Harris has posted Fraction Magic , an algorithm used to flip votes on Central tabulators.

Sensitivity analysis shows the effects of a range of assumptions on the vote count.

Let TV = True Vote; RV = Recorded vote
RV = TV + Fraud

Given the Recorded vote in millions:
Clinton 65.7, Trump 62.9, Other 7.6

Election fraud components:
-Vote flipping on maliciously coded, proprietary voting machines and central tabulators
-Illegal voters (non-citizens)
-Uncounted votes (spoiled ballots, disenfranchised voters)

Base Case Assumptions
Uncounted- 7 million: 85% for Clinton
Vote Flip- 5 million (net): 8% of Trump’s votes flipped to Clinton on voting machines and central tabulators. 
Illegals- 2 million: 85% for Clinton
Trump wins by 3.7 million: 68.7-64.9 (48.6-46.0%)

Assume 12 million uncounted: 85% to Clinton 
(2 million illegal, 5 million flip)
Trump still wins: 69.4-69.2 million (47.48-47.32%)

………..Total………Clinton….Trump……Other
Vote…..136.2……..65.7………62.9………7.6
Pct……,,100%..,….48.3%…..46.2%……5.6%

Illegal… 2.0…….  -1.70…..  -0.30…………0 non-citizens
Unctd…..7.0………5.95……..1.05…………0 disenfranchised 
Flip……..5.0…….  -5.0……….5.0………….0 voting machine

Net……141.2……64.9…….68.7………7.6
Adjusted………..46.0%….48.6%……5.4%

Sensitivity Analysis (assume 7 million uncounted, 85% for Clinton)
Worst case (7% flip, 80% of illegals to Clinton):  Trump wins by 2.3 million
Base case: (8%  flip, 85% of illegals to Clinton): Trump wins by 3.7 million
Best case: (9% flip, 90% of illegals to Clinton): Trump wins by 5.2 million

View the spreadsheet:  https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1672204415

http://www.pewhispanic.org/2016/01/19/millennials-make-up-almost-half-of-latino-eligible-voters-in-2016/ph_election-2016_chap1-chart-08/

	Total	Clinton	Trump	Other
Recorded vote	136.2 million	65.7	62.9	7.6
		48.25%	46.17%	5.59%
Illegal	2.0	-1.7	-0.3	0
Uncounted	7.0	5.95	1.05	0
Vote Flip	5.0	-5.0	5.0	0
Adjusted	141.22	64.9	68.7	7.6
		46.0%	48.6%	5.4%
	7.0 million uncounted	85% to Clinton
		Illegals to	Clinton
		80%	85%	90%
	Flip to Clinton		Trump Vote
	9%	69.20	69.30	69.40
	8%	68.57	68.67	68.77
	7%	67.94	68.04	68.14
	Vote Flip		Trump Vote
	9%	49.00%	49.07%	49.14%
	8%	48.56%	48.63%	48.70%
	7%	48.11%	48.18%	48.25%
	Vote Flip		Clinton vote
	9%	45.61%	45.54%	45.47%
	8%	46.06%	45.98%	45.91%
	7%	46.50%	46.43%	46.36%
	Vote Flip		Trump margin
	9%	4.79	4.99	5.19
	8%	3.53	3.73	3.93
	7%	2.27	2.47	2.67

 

University of Virginia Study: 20% of Trump Voters were former Obama Voters

Richard Charnin
April 29, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

University of Virginia Study: 20%  of 63 million Trump Voters were former Obama Voters

Larry Sabato is the founder and director of the Center for Politics at the University of Virginia.  http://www.thegatewaypundit.com/2017/04/larry-sabato-20-trump-voters-former-obama-voters-video/

Sabato said: “This is the largest study of just Trump voters… The first thing that is perfectly clear is that Trump has lost almost none of his backers, which includes the soft Trump voters. He’s still got 92-93% of them supporting him. It’s also true he hasn’t gained many people from the other side. We live in a very polarized era… What I found fascinating, nobody else has identified this, 20% of Trump voters actually voted for Obama either in 2008 or in 2012 or in both years. In other words a fifth of his vote came from Obama voters”.

Based on 2012 and 2016 recorded votes,  approximately 18.6% (11.68 million) of  62.9 million Trump voters were returning Obama voters.

 

2012	Pct	Trump	Clinton	Other	TrumpVote
Obama	51.03%	16.8%	81.0%	2.2%	11.68
Romney	47.19%	78.0%	13.0%	9.0%	50.13
Other	1.70%	45.0%	43.0%	12.0%	1.04
New	0.08%	44.0%	46.0%	10.0%	0.05
Total	100%	46.18%	48.24%	5.58%	62.90
Votes	136.20	62.90	65.70	7.60

https://richardcharnin.wordpress.com/2016/12/30/why-the-recorded-vote-and-unadjusted-exit-polls-are-wrong/

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=0

 

MY COMMENTS TO THE MSM ON THE RIGGING OF THE 2016 PRE-ELECTION POLLS

Richard Charnin
April 24, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

The MSM just interviewed the authors of  Shattered: Inside Hillary Clinton’s Doomed Campaign on the reasons for Clinton’s loss.  I commented to Chris Mathews and Brian Williams of MSNBC as well as FOX and CBS on how MSM pollsters rigged the pre-election polls for Clinton.

FYI: Your guests may not have looked at my 2016 Election model. It was based adjustments to final pre-election polls which were biased for Clinton. The Democratic Party-ID share was overstated at the expense of Independents who went solidly for Trump. In addition, there is strong evidence that votes were stolen from Jill Stein – by Clinton.

The 2016 Model projected Trump’s 306 RECORDED EV. But he actually had approximately 351 TRUE EV after adjusting for late undecided voters. https://richardcharnin.wordpress.com/2016/11/07/2016-election-model-forecast/

Recorded Vote: Clinton 48.3-46.2%, Trump 306-232 EV
Recorded Vote Forecast: Trump 44.4-42.9% with 306-232 EV
True Vote Model: Trump 48.5-44.3% with 351-187 EV

Note: I exactly forecast the RECORDED EV in the last three elections: 365, 332, 306. In each case the winner did better in the True Vote than the Recorded vote.

Here is the proof: https://richardcharnin.wordpress.com/2014/09/14/summary-2004-2012-election-forecast-1968-2012-true-vote-model/

 

 

 

 

2016 Voter Turnout and Vote share Sensitivity Analysis: Trump won the Popular Vote

Richard Charnin
Mar. 15, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Trump wins all 25 scenarios over various combinations of voter turnout

Assumption
Party ID (registration) 38I-31D-27R
(Gallup voter affiliation survey average Nov.1-13,  2016)

1. Base Case Voter Turnout: Dem 65%, Rep 70%, Ind 70%
Trump 48.3-45.2% (4.2 million vote margin)

2. Worst Case Turnout: Dem 67%, Rep 68%, Ind 70%
Trump 47.6-45.9% (2.3 million vote margin)

3. Best Case Turnout: Dem 63%, Rep 72%, Ind 70%
Trump 49.1-44.5% (6.2 million vote margin)

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=610568510

Reg Voter	Gallup	Base Case
Turnout	Voter Affil	Clinton	Trump	Johnson	Stein
70% Ind	38%	40%	50%	5%	5%
65% Dem	31%	88%	8%	1%	3%
70% Rep	27%	7%	89%	3%	1%
Vote share	100.0%	45.2%	48.3%	3.2%	3.2%
Votes	136.2	61.6	65.8	4.4	4.4
		Trump %
Dem		Rep Turnout
Turnout	68%	69%	70%	71%	72%
63%	48.3%	48.5%	48.7%	48.9%	49.1%
64%	48.2%	48.3%	48.5%	48.7%	48.9%
65%	48.0%	48.2%	48.3%	48.5%	48.7%
66%	47.8%	48.0%	48.2%	48.3%	48.5%
67%	47.6%	47.8%	48.0%	48.2%	48.3%
		Trump Vote
Dem		Rep Turnout
Turnout	68%	69%	70%	71%	72%
63%	65.9	66.1	66.3	66.6	66.8
64%	65.6	65.8	66.1	66.3	66.6
65%	65.4	65.6	65.8	66.1	66.3
66%	65.1	65.3	65.6	65.8	66.1
67%	64.9	65.1	65.3	65.6	65.8
		Clinton %
Dem		Rep Turnout
Turnout	68%	69%	70%	71%	72%
63%	45.2%	45.0%	44.9%	44.7%	44.5%
64%	45.4%	45.2%	45.1%	44.9%	44.7%
65%	45.6%	45.4%	45.2%	45.1%	44.9%
66%	45.8%	45.6%	45.4%	45.2%	45.1%
67%	45.9%	45.8%	45.6%	45.4%	45.2%
		Trump %	Margin
Dem		Rep Turnout
Turnout	68%	69%	70%	71%	72%
63%	3.1%	3.5%	3.8%	4.2%	4.5%
64%	2.8%	3.1%	3.5%	3.8%	4.2%
65%	2.4%	2.8%	3.1%	3.5%	3.8%
66%	2.0%	2.4%	2.7%	3.1%	3.4%
67%	1.7%	2.0%	2.4%	2.7%	3.1%
		Trump  Vote	Margin
Dem		Rep Turnout
Turnout	68%	69%	70%	71%	72%
63%	4.3	4.7	5.2	5.7	6.2
64%	3.8	4.2	4.7	5.2	5.7
65%	3.3	3.7	4.2	4.7	5.2
66%	2.8	3.3	3.7	4.2	4.7
67%	2.3	2.8	3.2	3.7	4.2

 

2016 True Vote Sensitivity analysis: illegal voters, uncounted votes, machine vote flipping

Richard Charnin
Updated Sept. 19, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Clinton won the recorded vote by 2.8 million. But the recorded vote is never equal to the True Vote due to election fraud.

There is evidence that millions of illegals probably voted in 2016. View this 1988-2016 trend analysis of Hispanic voter registration and turnout.

According to Greg Palast, least one million Democratic minority voters were disenfranchised via Crosscheck which eliminated voters with duplicate names from voter rolls. He claims that 7 million minority voters were disenfranchised.

There is evidence that  George Soros , a Clinton backer,  controls voting machines in 16 states.  Election analyst Bev Harris has posted Fraction Magic , an algorithm used to flip votes on Central tabulators.

Sensitivity analysis shows the effects of a range of assumptions on the vote count.

Let TV = True Vote; RV = Recorded vote
RV = TV + Fraud

Given the Recorded vote in millions:
Clinton 65.7, Trump 62.9, Other 7.6

Election fraud components:
-Vote flipping on maliciously coded, proprietary voting machines and central tabulators
-Illegal voters (non-citizens)
-Uncounted votes (spoiled ballots, disenfranchised voters)

Base Case Assumptions
Uncounted- 7 million: 85% for Clinton
Vote Flip- 5 million (net): 8% of Trump’s votes flipped to Clinton on voting machines and central tabulators. 
Illegals- 2 million: 85% for Clinton
Trump wins by 3.7 million: 68.7-64.9 (48.6-46.0%)

Sensitivity Analysis (assume 7 million uncounted, 85% for Clinton)
Worst case (7% flip, 80% of illegals to Clinton):  Trump wins by 2.3 million
Base case: (8%  flip, 85% of illegals to Clinton): Trump wins by 3.7 million
Best case: (9% flip, 90% of illegals to Clinton): Trump wins by 5.2 million

View the spreadsheet: https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1672204415

http://www.pewhispanic.org/2016/01/19/millennials-make-up-almost-half-of-latino-eligible-voters-in-2016/ph_election-2016_chap1-chart-08/

	Total	Clinton	Trump	Other
Recorded vote	136.22	65.72	62.89	7.61
		48.25%	46.17%	5.59%
Illegal	2.0	-1.7	-0.3	0
Uncounted	7.0	5.95	1.05	0
Vote Flip	5.0	-5.0	5.0	0
Adjusted	141.22	64.9	68.7	7.6
		46.0%	48.6%	5.4%
	7.0 uncounted	85% to Clinton
		Illegals to	Clinton
		80%	85%	90%
	Flip to Clinton		Trump Vote
	9%	69.20	69.30	69.40
	8%	68.57	68.67	68.77
	7%	67.94	68.04	68.14
	Vote Flip		Trump Vote
	9%	49.00%	49.07%	49.14%
	8%	48.56%	48.63%	48.70%
	7%	48.11%	48.18%	48.25%
	Vote Flip		Clinton vote
	9%	45.61%	45.54%	45.47%
	8%	46.06%	45.98%	45.91%
	7%	46.50%	46.43%	46.36%
	Vote Flip		Trump margin
	9%	4.79	4.99	5.19
	8%	3.53	3.73	3.93
	7%	2.27	2.47	2.67

 

Probability of exactly forecasting the electoral vote in the last three elections

Richard Charnin
Feb. 11, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

I was asked to calculate the probability of my exact forecast of the Electoral Vote in the last three elections (365,332,306). It was a combination of experience and luck. I do not expect to exactly forecast the EV in 2020.

My Track Record
https://richardcharnin.wordpress.com/2014/09/14/summary-2004-2012-election-forecast-1968-2012-true-vote-model/

Note that the following calculation is just an approximation.

Assume the following:
1) the probability of Obama winning in 2008 was 0.95; it was also 0.95 in 2012. The probability of Trump winning in 2016 was 0.05.
Therefore the probability of forecasting all three winners correctly is
P1 = 0.045 =.95*.95*.05

2) the winning EV is in the 270-370 range.
The probability of exactly forecasting the EV in a given election is 0.01. The probability of exactly forecasting the EV in all 3 elections is 1 in a million:
P2 =.000001 = 0.01*0.01*0.01

Therefore, the probability of forecasting the winner and the EV in the three elections is
P3 = P1*P2 = .045* 0.000001 or 1 in 22 million.

To put it another way, forecasting the electoral vote exactly in three successive elections would be expected to occur just once in 22 million elections (88 million years).

 

 

More clues on Election Fraud from Humboldt Cty, CA

Richard Charnin
Jan.1, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Humboldt is the gift that keeps on giving. It is the only county in the U.S. which uses an Open Source System (TEVS) to count and audit votes. The system was installed in 2006.

In the CA primary, Bernie Sanders had his highest share (71%) in Humboldt.

Bernie Landslide in CA Humboldt Cty (Open Source system)

In the 2016 presidential election, Jill Stein’s 6.1% Humboldt share was her highest in the state – just like it was for Bernie. Clinton’s 56% share in Humboldt ranked #20 of 58 California counties.

Stein’s average in the 19 counties was 2.3%. Clinton averaged 68.0%. So how come Stein did 4% better in Humboldt than she did in the other 19 liberal counties? And Clinton did 12% worse?

Did Jill Stein actually have an approximate 6% True vote in liberal CA? Did she have 4% nationally? Who believes she had just 1%? Just asking.

Could it be that fraud was prevented in Humboldt? Were nearly 2/3 of Stein’s votes blue-shifted to Clinton? Was Clinton’s 61% CA share inflated by at least 4%? Note that 4% of 14 million CA votes is 560,000. That’s a 1.2 million difference in vote margin. She won the national recorded vote by 2.8 million.

BUT THE RECORDED VOTE IS NEVER EQUAL TO THE TRUE VOTE.

In 2008-2012, Obama did 2.58% better in Humboldt than he did in the state. This is to be expected. But in 2016, Clinton did 1.75% worse in Humboldt while her 4.26% increase over Obama in CA represents a 1.2 million increase in vote margin. This is counter-intuitive. How did Clinton get all those votes? Was she really that popular? Or was her vote padded?

There is always election fraud. But in Humboldt, we can assume that the recorded vote is the True Vote due to its near foolproof Open Source system. There is no reason to believe Clinton’s recorded CA vote is legitimate.

Humboldt Democratic 2-party share
1988-2004 Before TEVS: 57.2%
2008-2016 After TEVS: 64.6%

California Presidential share
……Dem… Rep…Other
2008 60.21% 36.46% 3.33%
2012 60.24% 37.12% 2.64%
2016 61.73% 31.62% 6.66% HRC margin 7% over Obama?

Humboldt Presidential share
……Dem… Rep…Other
2008 62.05% 33.95%.4.00%
2012 59.68% 32.61% 7.72%
2016 56.04% 31.01% 12.95% HRC loses 3.64% vs Trump 1.60%

Democratic 2-party Presidential share
……CA….Humboldt..Diff
2008 62.28% 64.64% 2.36%
2012 61.87% 64.67% 2.80%
2016 66.13% 64.37% -1.75% HRC gains 4.26% over Obama?

…………………. Stein Clinton
1 San Francisco.. 2.4% 85.0%
2 Alameda……… 2.7  78.7
3 Marin…………..2.2  78.1
4 San Mateo……..1.6  75.7
5 Santa Cruz……..3.5  73.9
6 Santa Clara…….1.8  72.7
7 Los Angeles……2.2  71.8
8 Sonoma……….. 3.2  69.4
9 Contra Costa…..1.9  68.5
10 Imperial……….1.6  67.9
11 Monterey………2.1  66.8
12 Yolo…………….2.2 66.7
13 Napa……………2.1  63.9
14 Solano………….1.7  61.6
15 Santa Barbara ..2.1  60.6
16 Mendocino…….5.6  58.9
17 Sacramento….. 1.8  58.3
18 San Benito……. 1.7 57.1
19 San Diego………1.8 56.3
20 Humboldt……..6.2 56.0

View this spreadsheet of 58 county votes. https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1462588532

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1010903783

 

Why the 2016 pre-election polls, unadjusted exit polls and recorded vote are all wrong

Richard Charnin
Dec.30, 2016

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

The 2016 election was different in kind from prior elections; the Democrat was the establishment candidate. It was established beyond a reasonable doubt that the primaries were stolen from Bernie Sanders by the DNC which colluded with the media.

Some analysts claim that the 2016 unadjusted state exit polls prove that the election was rigged for Trump. But just because the polls were excellent indicators of the True Vote in the past does not prove that they were accurate in 2016. 

Are we supposed to believe that the MSM would not rig the unadjusted exit polls to match the rigged  pre-election polls  to make it appear that Clinton was the winner?
https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=0
http://www.inquisitr.com/3692040/2016-presidential-polls-hillary-clinton-donald-trump-leading-battleground-states-win-lose/

Exit pollsters at  Edison Research never reveal the location of precincts, votes and survey results. The only way to prove that the unadjusted exit polls are correct (and the published results bogus) is 1) to reveal the complete exit poll timeline and the data for all precincts polled and 2) a True Vote analysis based on historical and current independent data.

True Vote analysis indicates that Trump won the popular and electoral vote and that pre-election and exit polls were rigged for Clinton by inflating Democratic Party-ID. True Vote Models were based on a) national Gallup Party-ID voter affiliation and b) returning 2012 voters.

As usual, state and national exit polls were forced to match the recorded vote. This was the first election in which the media discussed election fraud – but avoided the obvious U.S. suspects from prior elections and the rigged voting machines, illegal and disenfranchised voters. Now that the MSM finally admits election fraud, they blame it on the Russians! And don’t report the proven fact that the primary was rigged for Clinton.

Party-ID
Nine Pre-election polls (average): 28.8 Ind – 38.7 Dem- 31.9 Rep.
Final National Exit Poll (CNN): 31 Ind – 36 Dem – 33 Rep.
Gallup national voter affiliation survey: 40 Ind -32 Dem -28 Rep. https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=505041111

Nine Pre-election polls 
Clinton won the average: 45.8-43.3%
Trump won the average Gallup-adjusted poll: 44.4-42.9%
Trump won Independents: 43.6-33.8%

Final  National Exit Poll (forced to match the Recorded Vote)
Clinton won the reported vote: 48.2-46.2%.
Clinton won the National Exit Poll: 47.7-46.2%.
Trump won Independents by just 46-42% – a 5.8% discrepancy from the pre-election polls which he led by 9.8%. This anomaly is additional evidence that Trump won the True Vote.

Unadjusted exit polls (28 states)
Clinton won the polls: 49.6-43.6%
Clinton won the corresponding recorded vote: 49.3-45.2%

States not exit polled
Trump won: 50.4-43.7%

True Vote
Trump led the True Vote Model (three scenarios of his share of late undecided voters)
– Scenario I:  47.5-45.1%, 306 EV (50% undecided)
– Scenario II: 47.9-44.7%, 321 EV (60% undecided)
– Scenario III: 48.3-44.3%, 351 EV (70% undecided)

The True Vote Model analysis based on a plausible number of returning voters from the prior election  confirmed the three scenarios: https://richardcharnin.wordpress.com/2017/04/29/university-of-virginia-study-20-of-trump-voters-were-former-obama-voters/

The National Election Pool of six media giants funds exit pollster Edison Research. The published results are always forced to match the recorded vote which implies zero election fraud. But there is always election fraud.  Historically, unadjusted state and national exit polls always favored the Democratic candidate, but there was  a RED shift from the Democrat in the poll to the Republican in the recorded vote.

The True Vote Model indicates that the 1988-2008 unadjusted exit polls were accurate.

Summary: 1968-2020 Forecast/True Vote Model

 

2016 Cumulative Vote Shares: Illinois, Michigan, California

2016 Cumulative Vote Shares: Illinois, Michigan, California

Richard Charnin
Dec. 22, 2016

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

102 Illinois Counties: Cumulative Vote Shares

Trump won 91 of 102 counties
Illinois: 5,095,677 Votes, Clinton 58.4%-41.6%, Margin: 859,319
Cook County: 1,968,795 Votes, Clinton 77.6%-22.4%, Margin:1,088,369
Other 101: 3,126,882 Votes, Trump 53.7-46.3%, Margin: 229,050

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1076651857

83 Michigan Counties: Cumulative Vote Shares

Trump won 75 of 83 counties.
Clinton won Wayne County (Detroit) by 290,451 votes (69.4-30.1%)
Trump won the other 82 counties by 301,155 votes (54-46%)

NY Post Dec. 14, 2016:
“The Detroit News found voting scanning machines at 248 of the city’s 662 precincts — 37 percent — tabulated more ballots than the number of actual voters counted in the poll books.

“There’s always going to be small problems to some degree, but we didn’t expect the degree of problem we saw in Detroit. This isn’t normal,” Krista Haroutunian, chairwoman of the Wayne County Board of Canvassers, told the paper.”

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=65235688

https://docs.google.com/spreadsheets/d/e/2PACX-1vQJ4IiceZg07muhLrjITSiesptsTygA1vM3CXC7OZBN9wxxS_4_HDpj8ODf7qht3NpaqIuh_Nt02W6G/pubchart?oid=404714130&format=image

 

58 California Counties: Cumulative Vote Shares

Based on the following data, it is difficult to believe that Hillary won the state by 4.27 million votes. She won the national recorded vote by 2.8 million, so Trump won the other states by at least 1.5 million (and that is conservative).

– Clinton did 7.0% better in CA than Obama in 2012. Clinton won by 61.7-31.6%, a 30.1% margin (4.27 million votes). Obama won by 60.2-37.1%, a 23.1% margin (3.01 million votes). If Clinton’s margin was 23.1%, she would have won by 3.3 million votes.In the CNN final CA exit poll (matched to the reported vote), the Party-ID is 47D-23R-30I . Was Clinton more popular than Obama? Not plausible.

– When the CA final exit poll Party-ID is adjusted from 47D-23R-30I to 34.2D-22.3R-43.5I based on the change in national Party ID from 2014, Clinton wins CA by 56.1-36.5% (2.78 million votes).

– Humboldt County, CA is the only county in the U.S. which uses Open Source software to count and audit votes. In the CA primary, Sanders had his highest vote share (71%) in Humboldt. Jill Stein also had her highest share (6.2%) in Humboldt.

Is it just a coincidence that Bernie and Jill both had their highest vote shares in Humboldt? Or was it due to the foolproof Open Source voting system?

– Hillary had 56% in Humboldt, nearly 6% lower than her total CA share. It is a fact that Bernie was cheated in CA by massive fraud. Who is to say that Hillary did not also cheat in CA to pad her popular vote margin?

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1462588532