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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. It was a combination of experience and luck. I do not expect to exactly forecast the EV in 2020.

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).

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

 
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Posted by on February 11, 2017 in 2016 election

 

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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 margin (71%) in Humboldt. https://richardcharnin.wordpress.com/2016/07/02/bernie-landslide-in-ca-humboldt-cty-open-source-system/

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

In the 2016 presidential election, Jill Stein’s 6.1% share in Humboldt 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 so much better in Humboldt than she did in the other 19 liberal counties?

Could it be Humboldt’s nearly foolproof Open Source voting system? Could it be that fraud was prevented in Humboldt? Could it be that nearly 2/3 of Stein’s votes were blue-shifted to Clinton? Could it be that Clinton’s 61% CA share was inflated by at least 4%? Note that 4% of 14 million votes is 560,000.

Keep in mind that the recorded vote is never equal to the True Vote. 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

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Posted by on January 1, 2017 in 2016 election

 

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Why the recorded vote and unadjusted exit polls are 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

Some analysts claim that the 2016 unadjusted state exit polls prove that the election was rigged for Trump. I proved mathematically that in the 1988-2008 presidential elections, 274 unadjusted state and 6 national exit polls were accurate and reflected true voter intent. But just because the polls were excellent indicators of the True Vote in the past does not prove that they were accurate in 2016.

Basic analysis indicates Trump won the popular and electoral vote. Pre-election and exit polls were rigged for Clinton. Democratic Party-ID was inflated in the pre-election and exit polls.

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.

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.

I used the True Vote Model analysis based on a plausible number of returning voters from the prior election to prove the unadjusted exit polls were correct in 1988-2008. I used a True Vote Model analysis based on Gallup Party-ID voter affiliation to prove that the unadjusted polls were bogus in 2016.

The True Vote Model indicates that the 1988-2008 unadjusted exit polls were accurate.
https://richardcharnin.wordpress.com/2014/09/14/summary-2004-2012-election-forecast-1968-2012-true-vote-model/

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.

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: the rigged voting machines, illegal and disenfranchised voters. No, it was the Russians!

And we are 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

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)

 
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Posted by on December 30, 2016 in 2016 election

 

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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

 

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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

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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

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Posted by on December 22, 2016 in 2016 election

 

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Analysis of 28 State Exit Polls vs. Recorded Vote vs. True Vote

Richard Charnin
Updated: Dec. 14, 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

Only 28 states were exit polled.  This analysis shows why the unadjusted exit polls are not plausible. Trump won the True Vote. 
a) He won Independents by  7.7% over Clinton.
b) Independents outnumbered Democrats by 6.7%.

Methodology
The state Party-ID crosstab (reported vote) is the basis for the analysis.
Exit Polls: Reported Party-ID weights. Independent vote shares adjusted to force a match to the total exit poll shares.

True Vote Calculation
State Party-ID is based on the Gallup National voter affiliation survey.
Method 1- Reported vote shares (CNN).
Method 2- Vote shares calculated in the Election Model.

Summary (28 states)
Unadjusted exit polls: Clinton leads 47.6-44.6% (unweighted average)
Party-ID: 35.1D – 32.7R – 32.2I (Dems outnumber Independents by 2.9%)
Share of Independents: Clinton 44.0-Trump 40.6% (not plausible)

Reported Vote (CNN)
Trump 47.3-46.7% (unweighted average)
Party-ID: 35.1D – 32.7R – 32.2I (Dems outnumber Independents by 2.9%)
Share of Independents: Trump 48.0-Clinton 40.3% (plausible)

True Vote
Model 1: Trump 46.7-46.0% (unweighted, reported vote shares)
Model 2: Trump 48.4-43.8% (unweighted, Election Model shares)
Party-ID: 32.0D – 29.3R – 38.7I (Independents outnumber Dems by 6.7%)

States Flipped from the Reported to the True Vote
True Vote 1:
Trump to Clinton: PA and FL (42 EV)
Clinton to Trump: VA NV NH CO (39 EV)
True Vote 2:
Trump to Clinton: PA
Clinton to Trump: VA NV NH MN ME CO …. WA OR NM

Notes:
-The model is probably wrong on WA and OR flipping to Trump.
-Trump leads 51.2-43.8% in the 22 states (and  D.C.) which were not polled.
-Clinton won NY and CA by at least 5 million votes, almost double her 2.7 national margin. Her True Vote margin in NY and CA is approximately 2.5 million.

The calculations are displayed as follows:
Unadjusted ….. Reported…..True Vote
https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=0

Link to TDMS Research exit poll table
http://tdmsresearch.com/2016/11/10/2016-presidential-election-table/

 
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Posted by on December 13, 2016 in 2016 election

 

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2016 Election Scenario Analysis

Richard Charnin
Nov. 23, 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 Exit Poll
LINKS TO  POSTS

This is an analysis of four election scenarios. 

1. Gallup Party-ID and True Vote Model (TVM) vote shares
2. Gallup Party-ID and National Exit Poll (NEP) vote shares
3. NEP Party-ID and NEP vote shares
4. NEP Party-ID and TVM vote shares

It is a FACT: the Reported vote is NEVER equal to the True Vote. The pundits always brainwash the public into assuming that the Reported vote represents True voter intent. 

The National Exit Poll is always forced to match the Reported vote  (view Scenario 3).
NEP Party-ID is 36D-33R-31I.
Clinton leads Trump by 2.03 million votes: 47.7-46.2%.
Others (including Johnson and Stein) have just 6.1% combined. Stein has 1%.

The True Vote Model (Scenario 1) uses Gallup Party-ID: 40I-32D-28R.
Trump leads Clinton by 2.18 million votes: 45.7-44.0%.  How many of the Other 10.3% voted for Jill Stein? Surely more than 1%. Probably close to 5%.

It is clear that the third party vote is a key factor. Jill Stein had an implausibly low 1% share. Where did her votes go?  Compare Trump’s 2.18 million True Vote margin in Scenario 1, in which third parties had 10.3%, to his negative margins in scenarios 2 and 3 where third parties had 6-7%. The differential  indicates that Stein did better than 1%. Her votes were stolen.

Exit poll discrepancies: http://tdmsresearch.com/wp-content/uploads/2016/11/2016-Presidential-Election-Table_Nov-17.-2016.jpg

 True Vote Sensitivity Analysis: Calculate Trump’s vote margins over a range of his shares of Republicans and Independents.

 1. Gallup/TVM  Party-ID Clinton Trump Other
Dem 32% 89% 9% 2%
Rep 28% 7% 90% 3%
Ind 40% 34% 44% 22%
TVM Total 100% 44.0% 45.7% 10.3%
Votes (mil) 133.26 58.69 60.87 13.70
2. Gallup/NEP   Party-ID Clinton Trump Other
Dem 32% 89% 8% 3%
Rep 28% 8% 88% 4%
Ind 40% 42% 46% 12%
Total 100% 47.5% 45.6% 6.9%
Votes (mil) 133.26 63.33 60.77 9.17
3. NEP/NEP Party-ID Clinton Trump Other
Dem 36% 89% 8% 3%
Rep 33% 8% 88% 4%
Ind 31% 42% 46% 12%
Total 100% 47.7% 46.2% 6.1%
Votes (mil) 133.26 63.57 61.54 8.16
4. NEP/TVM Party-ID Clinton Trump Other
Dem 36% 89% 9% 2%
Rep 33% 7% 90% 3%
Ind 31% 34% 44% 22%
Total 100% 44.9% 46.6% 8.5%
Votes (mil) 133.26 59.82 62.07 11.37

True Vote Model Sensitivity Analysis

Scenario 1 Trump % Rep
Trump 85.0% 87.0% 89.0% 91.0% 93.0%
% Ind Trump
48% 46.2% 46.7% 47.3% 47.8% 48.4%
44% 44.6% 45.1% 45.7% 46.2% 46.8%
40% 43.0% 43.5% 44.1% 44.6% 45.2%
Clinton
48% 43.6% 43.0% 42.4% 41.9% 41.3%
44% 45.2% 44.6% 44.0% 43.5% 42.9%
40% 46.8% 46.2% 45.6% 45.1% 44.5%
 Share Margin
48% 2.6% 3.7% 4.8% 6.0% 7.1%
44% -0.6% 0.5% 1.6% 2.8% 3.9%
40% -3.8% -2.7% -1.6% -0.4% 0.7%
 Vote (000)  Margin 
48% 3.5 5.0 6.4 7.9 9.4
44% -0.8 0.7 2.2 3.7 5.2
40% -5.1 -3.6 -2.1 -0.6 0.9

Summary Comparison (based on Party-ID)

Unadjusted Exit Poll   Reported Vote   True Vote  
Vote Clinton Trump Clinton Trump Clinton Trump
Avg 48.4% 45.8% 46.1% 49.6% 44.6% 48.4%
Diff   -2.6%   3.5%   3.9%
OH 47.0% 47.1% 43.5% 52.1% 43.9% 51.4%
NC * 48.6% 46.5% 46.7% 50.5% 45.9% 46.6%
NJ 59.8% 35.8% 55.0% 41.8% 44.6% 46.4%
PA * 50.5% 46.1% 47.7% 48.8% 47.8% 45.8%
MI 46.8% 46.8% 47.5% 47.7% 45.3% 47.8%
MO 42.8% 51.2% 38.0% 57.1% 41.5% 51.7%
IA 44.1% 48.0% 42.2% 51.8% 41.1% 50.6%
FL * 47.7% 46.4% 47.8% 49.1% 45.9% 47.7%
WI * 48.2% 44.3% 46.9% 47.9% 48.2% 45.2%
Share of  Indep-endents       
Unadjusted Exit Poll   Reported Vote   True Vote  
Clinton Trump Clinton Trump Clinton Trump
Avg 47.3% 40.3% 39.2% 53.1% 36.1% 50.2%
Diff   -7.0%   13.9%   14.1%
OH 50.0% 34.0% 38.0% 52.0% 38.0% 52.0%
NC 44.0% 44.0% 38.5% 56.0% 35.0% 49.0%
NJ 67.0% 28.0% 51.0% 48.0% 36.0% 52.0%
PA 50.0% 43.0% 36.0% 56.0% 32.0% 53.0%
MI 32.0% 52.7% 35.0% 56.3% 45.0% 56.3%
MO 45.0% 40.0% 28.0% 62.0% 39.0% 45.0%
IA 42.0% 41.0% 35.0% 51.0% 35.0% 51.0%
FL 48.0% 43.0% 48.0% 50.5% 32.0% 53.0%
WI 48.0% 37.0% 43.0% 46.0% 43.0% x46.0%
 
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Posted by on November 23, 2016 in 2016 election, Uncategorized

 

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