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Nevada: Recorded Vote vs. Exit Poll vs. True Vote

Nevada: Recorded Vote vs. Exit Poll vs. True Vote

Richard Charnin
Dec. 8, 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

Clinton won Nevada by 27,000 votes (47.9-45.5%).
She led the exit poll by 50.4-43.2% (86,000 votes)
The True Vote Model indicates that Trump won by 19,000 votes (47.2-45.4)
https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=0

The unadjusted NV exit poll is implausible based on two factors:
1) The Democratic Party-ID share (36D-28R-36I) is inflated. True Party-ID  is derived from the Gallup voter affiliation survey (40I- 32D- 28R). It is estimated as 31.3D -27.5R -41.2I.
2) Clinton’s  45-43% winning margin  of Independents required to match the “unadjusted” exit poll is implausibly high. Trump won Independents by 50-37% in the NV exit poll (matched to the recorded vote)  and by 48-44% nationally.

Summary Statistics

NV Unadjusted exit poll
Clinton wins: 50.4-43.2% (86,000 vote margin)
Clinton won Independents: 45-43%
Party ID: 36D- 28R- 36I

NV Reported Vote (CNN)
Clinton won: 47.9-45.5% (27,000 vote margin)
Trump won Independents: 50-37%
Party ID: 36D- 28R- 36I

NV True Vote Model
Trump wins 47.2-45.4% (19,000 vote margin)
Trump wins Independents: 50-36%
Party ID: 31.3D -27.5R -41.2I (derived from Gallup)

http://www.cnn.com/election/results/states/nevada
http://tdmsresearch.com/2016/11/10/2016-presidential-election-table/

Nevada          
Unadj Exit Party-ID Clinton Trump Johnson Other
Dem 36.0% 90% 8% 1% 1%
Rep 28.0% 8% 88% 2% 2%
Ind 36.0% 45% 43% 6% 6%
Calc 100.0% 50.8% 43.0% 3.1% 3.1%
Unadjusted 100.0% 50.9% 43.2% 3.7% 2.2%
Votes (000) 1,113 567 481 41 24
    Margin -86 -7.7%  
Reported Party-ID Clinton Trump Johnson Other
Dem 36.0% 90% 8% 1% 1%
Rep 28.0% 8% 88% 2% 2%
Ind 36.0% 37% 50% 7% 6%
Calc 100.0% 48.0% 45.5% 3.4% 3.1%
Reported 100.0% 47.9% 45.5% 3.3% 3.3%
Votes (000) 1,113 538 511 37 27
    Margin -27 -2.4%
True Vote Party-ID Clinton Trump Johnson Other
Dem 31.3% 90% 8% 1% 1%
Rep 27.5% 8% 88% 2% 2%
Ind 41.2% 36% 50% 7% 7%
Calc 100.0% 45.2% 47.3% 3.7% 3.7%
TVM bef UVA 94.5% 42.7% 44.4% 4.7% 2.7%
True Vote 100.0% 45.4% 47.2% 4.7% 2.7%
Votes (000) 1,113 506 525 53 29
    Margin 19 1.8%  
 
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Posted by on December 8, 2016 in 2016 election

 

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Oct. 12, 2016: Online debates, focus groups and strange pre-election polls

Richard Charnin
Oct.12, 2016

Just published: 77 Billion to One: 2016 Election Fraud
Matrix of Deceit 
Proving Election Fraud

Trump led 77-22% in the latest online debate polls of 4 million respondents. He had 59% in the online polls after the first debate. Clinton won the CNN “scientific” poll  of 537 respondents by 57-34%.

But the CNN poll indicated  that Trump did better than expected (Better 63%; Worse 21%; Same 15%). This confirms Trump’s 18% improvement in the online polls from the first debate.

In a CNN focus group, a participant reported: After the debate, they asked all of us in the focus group if we were decided on a candidate. Out of 28 panel members, 5 said they were decided on Clinton, 2 said they were decided on Trump, and 12 said they were going to vote 3rd party. But once they saw the response, they reshot the segment and replaced “3rd party” with “still undecided”.

The Frank Luntz focus group came up with an interesting result to the question:Who are you willing to vote for? Four Clinton voters and five undecideds switched to Trump.

Before the debate Hillary: 8: Trump: 9. After: Hillary: 4; Trump: 18

The latest NBC/WSJ Poll of 447 likely voters shows Clinton surging to an 11 point lead.But just like the other mainstream media pre-election polls, Independent Party ID percentages conflict with the Gallup Party Affiliation Survey.

Is there an NBC pollster Conflict of interest?

NBC Party ID Clinton Trump Stein Johnson
Dem 43.0% 94.0% 4.0% 1.0% 1.0%
Rep 36.0% 4.0% 80.0% 1.0% 15.0%
Ind 12.0% 35.0% 37.0% 10.0% 18.0%
Match 91.0% 46.1% 35.0% 2.0% 8.0%
Poll 92.0% 46.0% 35.0% 2.0% 9.0%

Pre-election polls ask voters whether they lean to the Democrat or the Republican. But Bernie Sanders won the vast majority of Independents who will likely  vote for  Green Party candidate Jill Stein.

Estimated True Vote Model

Model Gallup Clinton Trump Stein Johnson
Dem 32.0% 80.0% 5.0% 10% 5.0%
Rep 28.0% 5.0% 85.0% 5.0% 5.0%
Ind 40.0% 20.0% 25.0% 50.0% 5.0%
VOTE 100.0% 35.0% 35.4% 24.6% 5.0%
Poll 92.0% 46.0% 35.0% 2.0% 9.0%
 
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Posted by on October 12, 2016 in 2016 election, Uncategorized

 

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2014 Election : Why won’t the National Election Pool Release UNADJUSTED exit polls?

Richard Charnin
Nov.8, 2014

2014 Election: Why won’t the National Election Pool Release UNADJUSTED exit polls?

Look inside the books:
Reclaiming Science:The JFK Conspiracy
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

JFK Blog Posts
Probability/ Statistical Analysis Spreadsheets:
JFK Calc: Suspicious Deaths, Source of Shots Surveys;
Election Fraud: True Vote Models, State and National Unadjusted Exit Polls

The analysis of 1988-2014 election anomalies has been proven beyond any doubt that Election Fraud is systemic. If the Democrats or the Republicans were interested in fair elections, election fraud would have been eliminated long ago.  This is apparent based on the historic overview and analysis of election fraud.

In 2012,  the National Election Pool (NEP)  came to realize that unadjusted polls were a clear indicator of fraud  so they just stopped polling in 19 states. And we only have  adjusted state and national exit polls, so that the ability to prove election fraud based on unadjusted exit polls and true vote analysis is reduced.

It’s not just the exit polls that are manipulated. Pre-election Registered Voter (RV) polls are reduced to a Likely Voter (LV) subset, eliminating many new, mostly Democratic voters, as noted by  Jonathan Simon: Vote Counts and Polls: An Insidious Feedback Loop

The pattern is repeated in every election cycle:  a) Registered Voter (RV) pre-election polls  are reduced to a Likely Voter (LV) subset (eliminate many new Democratic voters) and b) unadjusted exit polls are forced to match the recorded vote (4-5% red-shift to GOP).

In 2014, the Republicans won the House recorded vote by 52.3-46.6%. According to the final, adjusted National Exit poll, they won by 51.9-46.1%. The .01% difference in margin was not due to perfect polling of a fraud-free election. It was due to the standard procedure of matching the exit poll to a fraudulent recorded vote.

Final vote shares were calculated for all 2014 National Exit Poll categories. But the actual exit poll responses are adjusted to match the recorded vote. UNADJUSTED STATE AND NATIONAL EXIT POLLS ARE ALWAYS FORCED TO MATCH THE RECORDED VOTE. But we never get to see the unadjusted polls until years later, if then.

Therefore, voters must demand to view the unadjusted exit polls (including polled precincts).  To paraphrase Alec Baldwin in Glengary Glen Ross: The unadjusted national exit polls are gold, but you don’t get them. They’re for closers (the corporate media).

2014 National House Exit Poll

Gender...Mix...Dem... Rep..Other Margin
Men......49.0% 41.0% 57.0% 2.0% 16.0%
Women....51.0% 51.0% 47.0% 2.0% 4.0%
Total..........46.1% 51.9% 2.0% 5.8%
Recorded.......46.6% 52.3% 1.1% 5.7%
Diff............0.5% 0.4% 0.9% 0.1%


The unadjusted national exit polls and the aggregate of state exit polls (adjusted only for state voting population) have closely matched the True Vote Model in all presidential elections since 1988. The True Vote Model has the Democratic margin at 53-41%; the unadjusted state and national exit polls are identical: 52-42%.

The Democrats won the 1988-2008 recorded vote by just 2% (48-46%). There is a consistent 8% exit poll margin discrepancy from the recorded vote. But we don’t have the unadjusted 2014 National Exit Poll. Based on 1988-2008 margins, 2014 would be expected to show a 50-48% unadjusted (true) Democratic margin- and eliminate the 4% red shift to the GOP.

 

This is an excellent paper from mathematician Kathy Dopp:

Click to access USElections2014.pdf

TRACK RECORD
Election Model Forecast; Post-election True Vote Model

1988-2008 State and National Presidential True Vote Model https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGN3WEZNTUFaR0tfOHVXTzA1VGRsdHc#gid=0

1968-2012 National Presidential True Vote Model https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdFpDLXZmWUFFLUFQSTVjWXM2ZGtsV0E#gid=4

2004 (2-party vote shares)
Model: Kerry 51.8%, 337 EV (snapshot) https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGN3WEZNTUFaR0tfOHVXTzA1VGRsdHc#gid=0
State exit poll aggregate: 51.7%, 337 EV
Recorded Vote: 48.3%, 255 EV
True Vote Model: 53.6%, 364 EV

2008
Model: Obama 53.1%, 365.3 EV (simulation mean) http://www.richardcharnin.com/2008ElectionModel.htm
Recorded: 52.9%, 365 EV
State exit poll aggregate: 58.0%, 420 EV
True Vote Model: 58.0%, 420 EV

2012 (2-party state exit poll aggregate shares)
Model: Obama 51.6%, 332 EV (Snapshot) https://richardcharnin.wordpress.com/2012/10/17/update-daily-presidential-true-voteelection-fraud-forecast-model/
Recorded : 51.6%, 332 EV
True Vote Model: 55.2%, 380 EV

 
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Posted by on November 8, 2014 in 2014 Elections, Election Myths

 

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The Election Fraud Quiz II

The Election Fraud Quiz II

Richard Charnin
Sept. 23, 2013

1 The exit poll margin of error is not a function of
a) sample-size, b) 2-party poll share, c) national population size

2 In the 1988-2008 presidential elections, the Democrats won the recorded vote 48-46%. They won both the average unadjusted state and national exit polls by
a) 50-46%, b) 51-45%, c) 52-41%

3 In 2004 the percentage of living Bush 2000 voters required to match the recorded vote was
a) 96%, b) 98%, c) 110%

4 In 2000 the approximate number of uncounted votes was
a) 2, b) 4, c) 6 million

5 In 2008, Obama won by 52.9-45.6%. He led the unadjusted National Exit Poll (17,836 respondents) by
a) 53-45%, b) 58-40%, c) 61-37%

6 In 1988 Bush beat Dukakis by 7 million votes (53.4-45.6%). Dukakis won the National Exit Poll by
a) 49.9-49.1%, b) 50.7-48.3%, c) 51.0-48.0%

7 In 1988 the approximate number of uncounted votes was
a) 6, b) 9, c) 11 million

8 Of 274 state exit polls from 1988-2008, 135 exceeded the margin of error (14 expected). How many moved in favor of the GOP?
a) 85, b) 105, c) 131

9 Gore won the popular vote in 2000. In 2004, returning Nader voters were 5-1 for Kerry, new voters 3-2 for Kerry. In order for Bush to win, he must have won
a) 30% of returning Gore voters, b) 90% of returning Bush voters, c) both (a) and (b).

10 In 2008 Obama won 58% of the state exit poll aggregate. Given it was his True Vote, he had how many Electoral Votes?
a) 365, b) 395, c) 420

11 What is the probability that 131 of 274 state exit polls from 1988-2008 would red-shift to the GOP beyond the margin of error?
a) 1 in 1 million, b) 1 in 1 trillion, c) 1 in 1 trillion trillion trillion trillion trillion trillion trillion trillion trillion (E-116)

12 In 2000 12 states flipped from Gore in the exit polls to Bush in the recorded vote. Gore would have won the election if he had won
a) 1, b) 2, c) 3 of the 12 states

13 In 1988 24 states had exit polls (2/3 of the total recorded vote). Dukakis won the state polls by
a) 50-49%, b) 51-48%, c) 52-47%

14 Exit polls are always adjusted to conform to the recorded vote. It is standard operating procedure and
a) reported by the corporate media, b) noted by academia, c) statistical proof of election fraud

15 Bush had 50.5 million votes in 2000. Approximately 2.5 million died and 1 million did not return to vote in 2004. Therefore, there could not have been more than 47 million returning Bush 2000 voters. But the 2004 National Exit Poll indicated 52.6 million returning Bush voters. This is proof that
a) Bush stole the 2004 election, b) it was a clerical error, c) 6 million Bush votes were not recorded in 2000.

16 In 2000 Gore won the popular vote by 540,000 votes (48.4-47.9%). He won the unadjusted state exit poll aggregate by 50.8-44.4% and the unadjusted National Exit Poll by 48.5-46.3%, indicating that
a) the state exit poll aggregate was outside the margin of error, b) the National poll was within the margin of error, c) the election was stolen, d) all

17 Corporate media websites show that Bush won the 2004 National Exit Poll (13660 respondents) by 51-48%, matching the recorded vote. But the unadjusted National Exit Poll indicates that Kerry won by 51.0-47.6% (7064-6414 respondents). The discrepancy is proof that
a) the poll was adjusted to match the recorded vote, b) Bush stole the election, c) both, d) neither

18 The pervasive difference between the exit polls and the recorded vote in every election is due to
a) inexperienced pollsters, b) Republican reluctance to be polled, c) systemic election fraud

19 In 1992 Clinton defeated Bush by 43-37.5% (Perot had 19.5%). Clinton won the unadjusted National exit poll by 48-32-20%. Bush needed 119% turnout of returning 1988 Bush voters to match the recorded vote. These anomalies were due to
a) bad polling, b) Bush voters refused to be polled, c) Bush tried but failed to steal the election.

20 Sensitivity analysis is a useful tool for gauging the effects of
a) various turnout assumptions, b) various vote share assumptions, c) both, d) neither

21 Monte Carlo simulation is a useful tool for
a) predicting the recorded vote, b) electoral vote, c) probability of winning the electoral vote.

22 The expected electoral vote is based on
a) state win probabilities, b) state electoral votes, c) both, d) neither

23 To match the recorded vote, which exit poll crosstab weights and shares are adjusted?
a) when decided, b) how voted in prior election, c) party ID, d) gender, e) education, f) income, g) all

24 In 2004 Bush’s final pre-election approval rating was 48%, but it was 53% in the adjusted National Exit Poll. The discrepancy was due to
a) late change in approval, b) different polls, c) forcing the exit poll to match the recorded vote

25 The True Vote Model is designed to calculate the fraud-free vote. The TVM utilizes final exit poll shares but estimates returning voters based on the prior election
a) recorded vote, b) votes cast, c) unadjusted exit poll, d) true vote, e) all

https://richardcharnin.wordpress.com/category/true-vote-models/

1c 2c 3c 4c 5c 6a 7c 8c 9c 10c 11c 12a 13c 14c 15a 16c 17c 18c 19c 20c 21c 22c 23g 24c 25e

 

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Debunking a JFK Mysterious Witness Death Lone Nutter

Debunking a JFK Mysterious Witness Death Lone Nutter

Richard Charnin
Aug. 6, 2013
Updated: March 8, 2014

Click Reclaiming Science:The JFK Conspiracy to look inside the book.

JFK Blog Posts
JFK Calc Spreadsheet Database

This post will debunk the following article on JFK witness deaths: http://www.vectorsite.net/twjfk_32.html

The author writes:
As something of a footnote, conspiracists have long played up the number of “mysterious deaths” associated with the JFK assassination, though an inspection of the list makes it seem substantially less mysterious. In any case, the bottom line of a half-century’s investigation of the assassination is that we are left with the conclusion that was apparent from the start: JFK was killed by a lone assassin named Lee Harvey Oswald.

One of the most preposterous claims of the conspiracists is that there have been large numbers of “mysterious deaths” of witnesses relevant to the JFK assassination. Jim Marrs, in his 1993 book (sic 1989) CROSSFIRE, cited 103 “mysterious deaths” up to 1984.

Conspiracists assert that odds of such groupings of deaths are so low that it is impossible to believe they couldn’t have been part of a plan, in particular citing a 1967 LONDON SUNDAY TIMES article with an early “mysterious deaths” list accompanied by a claim that an actuary had calculated the odds to be “a hundred thousand trillion to one”.

The HSCA found this citation of odds a little hard to believe. The list of people who could be connected to the JFK assassination was long, easily running to thousands, and the idea that a portion of them might have died over some period of years hardly seemed that improbable. The HSCA contacted the TIMES and got back a sheepish answer. It turned out that the question the paper had asked of an actuary was effectively:

Name 15 specific adults selected at random from the population of the USA. What are the odds that all 15 of these named people will be dead within a few years?

The odds are not at all good. Assume that adults in a population have, on the average, a 1 in 10 probability of dying in some given number of years. If 15 adults are selected at random from that population, the odds of all 15 dying to that time would be 1 in 10^15, a thousand trillion to one.

However, anybody with even a simple understanding of probability would know that was asking the wrong question. The right question was obviously: Given a group of several thousand people, what are the odds that at least 15 unspecified members of that group will be dead in a few years?

The answer was that one could bet on it and easily win. Given 1 in 10 odds of an adult in a population dying in some given number of years, we would expect in that time that, duh, roughly a tenth of the population would be dead. The TIMES apologized to the HSCA for the blunder.

——————————————————

The article is a total fiasco

The Lone Nutter’s ignorance and naivete is confirmed by this utterly false statement: “However, anybody with even a simple understanding of probability would know that was asking the wrong question. The right question was obviously: Given a group of several thousand people, what are the odds that at least 15 unspecified members of that group will be dead in a few years? The answer was that one could bet on it and easily win. Given 1 in 10 odds of an adult in a population dying in some given number of years, we would expect in that time that, duh, roughly a tenth of the population would be dead.”

The author calls legitimate seekers of the truth “conspiracists”. But he does not understand the problem, much less the math. This is the correct definition: Given a group of N people, what is the probability that at least n members of the group will die unnaturally (homicide, accident or suicide) within T years?

He just repeats the usual Warren Commission apologist talking points. The mathematical proof of a conspiracy relegates his screed as pure propaganda. Lone Nutters are shameless and have no regard for the truth.

The author’s lack of specificity is the “tell”. He fails to consider any of the following critical factors: the total number of material witnesses in the group, the number and cause of unnatural deaths, the time interval, unnatural mortality rates. All are necessary input for the probability calculation.

This LN does not even qualify as an amateur. But that’s understandable. After all, he’s a Lone Nutter, who by definition is incapable of rational analysis.

His logical errors and omission of key factors in his “analysis” include:
1) not assuming a specific number of witnesses in the target group,
2) invention of a 1 in 10 probability of dying,
3) not assuming a definitive time period,
4) failure to consider unnatural deaths and related mortality stats,
5) use of a pathetically, unscientific probability calculation,
6) naively states that “roughly a tenth of the population would be dead”.
7) failure to refute the relevance of 100 “convenient” deaths
8) failure to consider the more than 60 deaths of witnesses sought to testify.
9) failure to correctly calculate the expected number of unnatural deaths:
E=N*T*R, where N =total witnesses in the group, T= time period, R= weighted average mortality rate.
10) failure to consider the “paradigm shift”: why the witnesses died is a non-factor. The only relevant factors are how many died unnaturally, the time interval and the universe of material witnesses or the number of witnesses called to testify.

There are 120 dead material witnesses in the JFK Calc spreadsheet database based on a 1400+ total universe. Of the 120, 63 were sought to testify at the Warren Commission, Garrison trial, Church Senate and HSCA.

The author does not consider that the number of UNNATURAL deaths among the 1400+ witnesses is the key factor – not total deaths. There was a STATISTICALLY IMPOSSIBLE 77 OFFICIALLY RULED UNNATURAL DEATHS (34 homicides, 24 accidents, 16 suicides, 3 unknown).

In fact, 25 of the 40 accidents and suicides were actually HOMICIDES – based on the STATISTICAL EXPECTATION of 12 accidents and 3 suicides – so we are up to 59 homicides among the 77 unnatural deaths. But by the same reasoning, there was a statistically impossible number of “natural deaths”: HEART ATTACKS and SUDDEN CANCERS. Therefore, the 34 OFFICIAL homicides UNDERSTATES the true number (estimated as 90+) based on STATISTICAL EXPECTATION.

These graphs are mathematical proof of a conspiracy.

The Paradigm Shift
But his most fundamental flaw was focusing on the relevance of individual witnesses in Marrs’ list without considering the paradigm shift: WHY the witnesses died is IRRELEVANT.

The relevant factors are how many witnesses were called to testify, how many died, their cause of death and the time period. In fact, from 1964-78, approximately 1100 witnesses were called to testify in four investigations. At least 63 died (38 unnaturally, including 27 homicides).

The author claims there were thousands of witnesses. In fact, the FBI claimed to have interviewed 25,000 (only about 1400 were material). But let’s assume there were 25,000.

There were at least 25 homicides of material witnesses from 1964-66. The probability of at least 25 homicides among the 25,000 is 1 in 38 BILLION (2.6E-11). The average homicide rate for 1964-66 was 0.000061.

There were at least 83 homicides from 1964-78. The probability of 83 homicides among the 25,000 is 1 in 43 TRILLION (2.32E-14). Only 32 homicides would normally be expected. The average homicide rate for 1964-78 was 0.000084.

The data and probabilities are displayed in JFK Calc: A Spreadsheet/Database of Mysterious Witness Deaths.

Statistically expected number of unnatural deaths
Expected unnatural deaths: E = N*T*R, where
N = 1400 material witnesses
T = 15 years (1964-78)
R = .000818 average unweighted unnatural mortality rate

JFK Material witnesses unnatural mortality
Among 1400 material witnesses from 1964-78, 77 deaths were officially ruled as unnatural – but only 17 were statistically expected: 34 homicides (2 expected); 24 accidents (12 expected); 16 suicides (3 expected) and 3 unknown (0.2 expected). There were 40 deaths officially ruled as accidental or suicide – but only 15 were expected. Therefore it is likely that approximately 25 (40-15) accidents and suicides were actually homicides.

Expected vs. Official Unnatural Death (1964-78)

Cause Expected Official Mortality Rate
homicide 1.76 34 0.000084 44%
suicide. 2.91 16 0.000130 21%
accident 12.47 24 0.000594 31%
unknown. 0.21 3 0.000010 4%
Total 17.35 77 0.000818 100%

Warren Commission
According to the CIA, N= 418 witnesses testified, but the total was 552 including affidavits and depositions.

There were at least n= 18 unnatural deaths over T= 15 years (1964-78). The probability of at least 10 unnatural deaths among the witnesses in 3 years is:
P = 1 – poisson(9, 1.06, true) = 1.81E-07 (1 in 5,509,693)
(based on the 0.000842 national unnatural rate)
P = 1 – poisson(9, 0.31, true) = 1.53E-12 (1 in 652,270,204,558)
(based on the 0.000245 JFK witness-weighted unnatural rate)

The London Sunday Times Actuary
The actuary’s 100,000 trillion to one odds of 18 material witness deaths in three years (13 were unnatural) is matched by assuming 459 witnesses and the 0.000207 weighted unnatural mortality rate. Only one unnatural death would normally be expected among 459 witnesses in the three year period.
The probability is:
P= POISSON (13, 0.29, false) = 9.96E-18 (1 in 100,000 TRILLION)

This is a sensitivity analysis of unnatural witness deaths.

Convenient deaths spiked in 1964 (Warren Commission) and 1977 (House Select Committee).

 
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Posted by on August 6, 2013 in JFK

 

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2012 Election Fraud: A True Vote Model Proof

2012 Election Fraud: A True Vote Model Proof

Richard Charnin
Jan. 2, 2013
Updated: Aug.31, 2015

An objective analysis of the 2012 election shows that Obama must have done much better than his recorded margin. The 2012 True Vote Model indicates that Obama had an approximate 55-43% True Vote (a 15 million margin) and overcame the systemic 4-5% red-shift fraud factor. He won the recorded vote by just 51.0-47.2% (a 5.0 million margin) .

Media Gospel
Media pundits, academics and politicians are quick to accept the recorded result in every election as gospel. But the landslide was denied, just like it was in 2008 and six previous elections.

Exit pollsters always assume that both prior and current elections were fair but that the exit poll samples were biased. So they adjust exit poll weights and vote shares to match the sacrosanct recorded vote. They never consider the possibility that the exit poll sampling was good but that the elections were fraudulent.

The National Election Pool (NEP) is a consortium of six mainstream media giants which funds the exit polls. In 2012, just 31 states were polled. This effectively prevents a calculation of the total aggregate vote share.

Unadjusted 2012 state and national presidential exit polls have not been made available. Furthermore, in another omission, the How Voted in 2008 category was not included in the adjusted National Exit Poll demographic cross tabs displayed on media polling websites.

Is it just a coincidence that the past vote has consistently been a key factor in proving systemic election fraud in every election since 1988? In order to match the recorded vote in 1988, 1992, 2004 and 2008, the National Exit Poll indicated millions more returning Bush voters from the prior election than actually voted. 

Why does the NEP place such onerous restrictions on exit poll transparency?  It’s bad enough that analysts never get to view raw unadjusted exit poll data. Why is the NEP hiding this critical information? There can only be one reason: the data would provide absolute proof that the elections were fraudulent. If election fraud was non-existent, the data would have been released. But a robust statistical analysis of the red-shift to the GOP in state and national unadjusted exit polls proves beyond all doubt that election fraud is systemic.

Conspiracy Theory?
Those not convinced by the overwhelming statistical and factual evidence and still maintain that election fraud is just a conspiracy theory are welcome to try and refute the following analysis.

Naysayers claim that Obama stole the 2012 election. They cite as proof the fact that he won 100% of the vote in 59 black Philadelphia precincts. They consider it impossible. They are wrong. It is entirely possible. This math proof will put an end to this canard.

If the 2008 election was not fraudulent, then the 2008 recorded vote (Obama had 52.9%, a 9.5 million vote margin) is a reasonable basis for estimating returning voters in 2012. Assuming plausible vote shares applied to returning and new voters results in a close match to Obama’s recorded margin.

On the other hand, if the 2008 election was fraudulent, then Obama’s 2008 unadjusted state 58.0% exit poll aggregate, 61.0% unadjusted National Exit Poll and 58.0% True Vote Model shares were essentially correct. Using the 58.0% share as the basis for estimating returning voters in 2012 (and applying the same plausible vote shares as above) Obama won the 2012 True Vote by 56.1-43.9% (2-party), a 15.5 million margin.

There are some who believe that Election Fraud was thwarted in 2012 by the Anonymous hack or government oversight. These factors may have prevented some late vote-rigging. But the True Vote Model and Late Vote results were consistent with 2008. Vote switching algorithms were in effect on Election Day in most states. Why should 2012 have been any different?

Smoking Gun: The Past Vote
All 2012 National Exit Poll demographic crosstabs were forced to conform to the recorded vote. About 80 questions were posed to 25,000 respondents, but the most important one is missing: Who did you vote for in 2008? The past vote question was always asked before 2012. In at least four presidential elections (1988, 1992, 2004, and 2008), the returning voter mix displayed in the adjusted NEP was mathematically (and physically) impossible. Each poll indicated that there were millions more returning Bush voters from the previous election than were still living – a clear indication of a fraudulent vote count.

Problem:Calculate by trial and error the average number of voters per Philadelphia division required for Obama to have 100% in 59 divisions. Assume that Obama had 97% of blacks  in 1700 divisions, 59 of which  voted 100% for Obama

Calculate the probability that 100% of voters in 59 Philadelphia divisions voted for Obama. Estimate an average of 182 voters/division. The  Margin of Error=3.22% for N=182 voters; Obama 97% share; 0.3 Cluster effect. Then there is  a 3.4% (1 in 29) probability that a division voted 100% for Obama ( 59 total, where 59 = 1700/29.)

The 2012 True Vote Model rectifies the NEP return voter anomaly by calculating feasible estimates of returning voters from the prior election.

Sensitivity Analysis
Pollsters and pundits and academics never analyze alternative returning voter turnout and corresponding vote share scenarios. Is it because a sensitivity analysis would reveal scenarios that they would rather not talk discuss?

The 2012 True Vote Model base case assumed that:
1. Obama won the 2008 True Vote: 58%-40.3%
2. A 95% turnout of Obama and McCain voters in 2012
3. Obama had 90% of returning Obama voters;7% of McCain
4. Obama had 59% of new voters; McCain had 41%
In this base case scenario, Obama had a 56.1% (two-party) True Vote Share and won by 15.5 million votes.

Romney needed to win 18% of returning Obama voters and 93% of returning McCain voters in order to match the recorded share (given the 2008 voter turnout assumption). In other words, there had to be an implausible 11% net defection of Obama voters to Romney.

Given the base case vote assumptions, Romney needed an implausibly low 72% turnout of Obama 2008 voters and a 95% turnout of McCain voters in order to match the recorded vote.

2008 National Exit Poll
To put the base case assumptions in context, let’s review the 2008 National Exit Poll. Obama had 89% of returning Kerry voters, 17% of returning Bush voters and 72% of those who did not vote in 2004. In order to match the recorded vote (Obama by 52.9-45.6%), the poll indicated an impossible 46% (60.3 million) of the 2008 electorate were returning Bush voters and just 37% (48.6 million) were returning Kerry voters. It implies that 103% of living Bush 2004 voters returned to vote in 2008.

On the other hand, assume a) that Kerry won the 2004 True Vote by 53.7-45.3% and therefore b) 47.5% of the 2004 electorate were returning Kerry voters vs. 40% Bush voters, then Obama won by 23 million votes with a 58.0% share.

The Late Vote – a True Vote Confirmation
The recurring pattern of Democratic presidential late vote shares exceeding the Election Day shares by approximately 7% is further confirmation of fraud. In 2012, Obama led 50.3-48.1% in the 117.4 million votes cast early and on Election Day. But he had a whopping 58.0-38.3% margin in the 11.7 votes recorded Late. Nearly half of his total margin came from late votes.

In 2008, Obama had 59% of 10.2 million late votes compared to 52.4% of votes cast early or on Election Day. Is it just a coincidence that he won the 2008 unadjusted state aggregate exit polls by a nearly identical 58.0-40.5% and the National Exit Poll by 61.0-37.5%? In 2012, there were just 31 adjusted state exit polls; unadjusted state and national poll results have not been released.

But is the late vote a legitimate proxy of the True Vote? To find out, we need to weight (multiply) each state’s late vote share by its total vote. In 2008, Obama won the weighted aggregate state late vote by 57.4-38.6%, within 1% of the weighted state exit polls and the True Vote Model. In 2012, he won the late vote by 54.0-41.8%. The 12.2% margin exactly matched the 2-party True Vote Model (56.1-43.9%). The fact that the weighted late shares matched the True Vote Model in both 2008 and 2012 is compelling evidence that the Late vote is fairly representative of the electorate.

Given Obama’s 58.0-38% margin for the 11.7 million late votes, this 2012 Vote share sensitivity analysis displays his total vote share over a range of Early and Election Day vote shares.

Red Shift
There was an overwhelmingly one-sided exit poll red-shift to the Republicans in all presidential elections since 1988. The Democrats won the state and national unadjusted exit polls by 52-42%. The True Vote Model indicates a 53-41% margin, yet they won the official recorded vote by just 48-46%. The final published exit polls are always adjusted to match the recorded vote – come hell or high water.

National Exit Poll Crosstab Adjustments
The 2012 National Exit Poll Party-ID category indicates a 39D-32R-29I split. Was the unadjusted Democratic share lowered to force a match to the recorded vote?

Let’s consider the 2004 and 2008 elections.The 2008 unadjusted National Exit Poll indicated a 45.5D-27.3R-27.2I Party-ID split. It was adjusted to 39/32/29 to force a match to the recorded vote.

In 2004, the Democrats led the pre-election Party ID polling by 38-35-27. The split was changed to 37-37-26 in the adjusted NEP to force a match to the recorded vote.

In 2004, Bush had a 48% average approval rating in 11 pre-election polls and a 50% rating in the unadjusted state exit poll aggregate. The rating was adjusted to 53% in the National Exit Poll to match the recorded vote.


2012 True Vote Model
Voted...2008 2012 2-party vote shares
2008 Implied Votes Mix Obama Romney
DNV.......... 10.4 8.20% 59.0% 41.0%
Obama...58.0% 67.6 53.3% 90.0% 7.00%
McCain..40.4% 46.9 37.0% 7.00% 93.0%
Other...1.60% 1.90 1.50% 50.0% 50.0%

Total…100% 126.8 100% 56.1% 43.9%
Votes…………..126.8 71.1 55.7

2012 Sensitivity Analysis
….Pct of returning Obama
…. 82.5% 90.0% 92.0%
%McCain
…..Obama 2-party Share
10% 53.1% 57.2% 58.3%
7% 51.9% 56.1% 57.1%
4% 50.8% 54.9% 56.0%
……. Margin
10% 7.8 18.2 21.0
7% 5.0 15.4 18.1
4% 2.1 12.5 15.3

Sensitivity Analysis I: 2008 WAS FRAUDULENT
Obama had 58.0% (True Vote)
Obama had 7% of returning McCain voters

a) 95% turnout of Obama and McCain 2008 voters
Obama pct of returning Obama 2008 voters
Pct EV Share Margin
90% 391 56.06% 15,365 True Vote
88% 371 54.97% 12,614
86% 333 53.89% 9,864
84% 318 52.80% 7,113
82% 315 51.72% 4,362 Recorded

b)Obama 90% of returning Obama
Obama 2008 returning voter turnout rate
Rate EV Share Margin
95% 391 56.06% 15,365 True Vote
90% 371 55.05% 12,807
85% 333 53.95% 10,032
80% 318 52.77% 7,018
77% 318 52.00% 5,083 Recorded

Sensitivity Analysis II: 2008 WAS NOT FRAUDULENT
Obama had 52.9% (recorded)
Obama had 7% of returning McCain voters

a) 95% turnout of Obama and McCain 2008 voters
Obama pct of returning 2008 Obama voters
Pct EV Share Margin
91% 332 52.16% 5,491 Recorded
90% 303 51.67% 4,238
88% 285 50.68% 1,730
86% 272 49.69% -777
84% 253 48.71% -3,285

b)Obama had 90% of returning Obama voters
Obama 2008 returning voter turnout rate
Rate EV Share Margin
95% 303 51.67% 4,238 Recorded
93% 303 51.25% 3,177
91% 285 50.82% 2,087
89% 285 50.38% 964
87% 272 49.92% -191

Late Vote Confirms the True Vote
Year 2pty Obama Repub Other Margin
2008 59.8 57.4 38.6 4.0 18.8 late
2008 59.0 58.0 40.3 1.7 17.7 true
2012 56.4 54.0 41.8 4.2 12.2 late
2012 56.1 55.0 43.0 2.0 12.0 true

Unadjusted 2004 National Exit Poll
2004 Sample Kerry Bush Other
Total 13,660 7,064 6,414 182
Share 100.0% 51.8% 46.9% 1.3%

Unadjusted 2004 National Exit Poll
2000 Turnout Mix Kerry Bush Other
DNV 23,116 18.4% 57.0% 41.0% 2.0%
Gore 48,248 38.4% 91.0% 8.00% 1.0%
Bush 49,670 39.5% 10.0% 90.0% 0.0%
Other 4,703 3.70% 64.0% 17.0% 19.0%

Total 125.7 100% 51.8% 46.9% 1.3%
Votes…… 125.7 65.1 58.8 1.8

Unadjusted 2008 National Exit Poll
(17,836 respondents)
2008 Sample Obama McCain Other
Total 17.836 10,873 6,641 322
Share 100.0% 61.0% 37.2% 1.8%

2008 Party ID
2008 Sample Dem Rep Other
Total 17,774 8,096 4,851 4,827
Share 100.0% 45.5% 27.3% 27.2%

Final 2008 National Exit Poll
(forced to match recorded vote)
Voted…2004 2008
2004 Implied Votes Mix Obama McCain Other
DNV……….. 17.1 13.0% 71.0% 27.0% 2.0%
Kerry…42.5% 48.6 37.0% 89.0% 9.00% 2.0%
Bush….52.9% 60.5 46.0% 17.0% 82.0% 1.0%
Other…4.60% 5.30 4.00% 72.0% 26.0% 2.0%

Total…100% 131.5 100% 52.87% 45.60% 1.54%
Votes…………. 131.5 69.50 59.95 2.02

How Voted in 2004
Voted Kerry Bush Other DNV Total
2004….1,815 1,614 188 561 4,178
Share…43.5% 38.6% 4.5% 13.4% 100%

2008 Unadjusted National Exit Poll
Voted…2004 2008
2004 Implied Votes Mix Obama McCain Other
DNV……….. 17.7 13.4% 71.0% 27.0% 2.0%
Kerry…50.2% 57.1 43.5% 89.0% 9.00% 2.0%
Bush… 44.6% 50.8 38.6% 17.0% 82.0% 1.0%
Other…5.20% 5.92 4.50% 72.0% 26.0% 2.0%

Total…100% 131.5 100% 58.0% 40.4% 1.6%
Votes………….. 131.5 76.3 53.0 2.2

2008 True Vote Model
(Returning voters based on 2004 True Vote)
Voted…2004 2008
2004 True Votes Mix Obama McCain Other
DNV………. 15.3 11.6% 71.0% 27.0% 2.0%
Kerry…53.7% 62.4 47.5% 89.0% 9.00% 2.0%
Bush….45.3% 52.6 40.0% 17.0% 82.0% 1.0%
Other…1.00% 1.16 0.90% 72.0% 26.0% 2.0%

Total…100% 131.5 100% 58.0% 40.4% 1.6%
Votes…………. 131.5 76.2 53.2 2.1

____________________________________________________________________

Track Record: Election Model Forecast; Post-election True Vote Model

2004 Election Model (2-party shares)
Kerry:
Projected 51.8%, 337 EV (snapshot)
Recorded: 48.3%, 255 EV
State exit poll aggregate: 51.7%, 337 EV
True Vote Model: 53.6%, 364 EV

2006 Midterms
Regression Trend Model Projected Democratic Generic share: 56.43%
Unadjusted National Exit Poll: 56.37%

2008 Election Model
Obama
Projected: 53.1%, 365.3 EV (simulation mean);
Recorded: 52.9%, 365 EV
State exit poll aggregate: 58.0%, 420 EV
True Vote Model: 58.0%, 420 EV

2012 Election Model
Obama Projected: 51.6% (2-party), 332 EV snapshot; 320.7 expected; 321.6 mean
Adjusted National Exit Poll (recorded): 51.0-47.2%, 332 EV
True Vote Model 56.1%, 391 EV (snapshot); 385 EV (expected)
Unadjusted State Exit Polls: not released
Unadjusted National Exit Poll: not released

 
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Posted by on January 2, 2013 in 2012 Election, True Vote Models

 

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Matrix of Deceit: Election Myths, Logic and Probability of Fraud

Election Fraud: Uncertainty, Logic and Probability

Richard Charnin
Oct. 29, 2012

Everyone thinks about how to go about solve problems. But how can they be sure the methods used to solve them are valid? My new book Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts deals with uncertainty in our election systems. How do we know that the votes are counted as cast? If the information we are given is tainted, how do we know? We must distinguish between intuitive and logical reasoning. Decisions must be made where there are multiple solution methods.

Which make the most sense? Which is the most probable? If you flip a coin and it comes up heads five times in a row, is the next flip more likely to be tails? Is a baseball player with a .300 batting average who has not had a base hit in his last 10 at bats due to get one his next time up? In decision making, we always need to consider probabilities.

In mathematics we need unambiguous definitions and rules. In other words, we need logical thinking. Logic is defined as a systematic study of the conditions and procedures required to make valid inferences.

We start with a statement and infer other statements are valid and justified as a consequence of the initial statement. It is important to note that logical inference does not mean the statement is true, only that it is valid. If the starting statement is true, then a logically derived result must also be true.

For example, it is a statement of fact that Bush had 50.5 million recorded votes in 2000. Approximately 2.5 million Bush 2000 voters died prior to the 2004 election, so there could not have been more than 48 million returning Bush voters. But according to the 2004 National Exit Poll, there were 52.6 million returning Bush voters. This is clearly impossible.

Furthermore, since the 2004 National Exit Poll was impossible and adjusted to match the recorded vote, then the recorded vote must also have been impossible. This simple deductive reasoning proves 2004 Election Fraud. But the recorded 2000 vote was also fraudulent – as were all elections before that. None reflected true voter intent. The simple proof: there were 6-10 million uncounted votes in every election prior to 2004. Votes cast exceeded votes recorded by 6-10 million. And 70-80% of the uncounted votes were Democratic.

Each National Exit poll is forced to match the bogus recorded vote based on bogus returning voters from the prior bogus election. It’s a recursive process. The polls assume all elections are fair and accurate. The same returning voter logic applied to the 1988, 1992 and 2008 elections shows that they were also fraudulent; the National Exit Polls were forced to match the recorded vote by indicating there were more returning Bush voters than were alive to vote. The corporate media has never seen fit to explain these recurring impossibilities.

Science is “cumulative”. New developments may refine or extend past knowledge. There is no such thing as a foolproof system. What is needed is a probability-based system for many types of problems. It is the only rational way of thinking.

There is no way to eliminate all risk (error) in a system model (or election poll). The problem is to evaluate risk and measure it based on a probability analysis. Every important problem requires a comparison of the odds. Probability analysis supplements classical logical thinking but does not replace it. In fact, classical logic is required in every step in the development of probability theory.

Election Model Forecast; Post-election True Vote Model

2004 Election Model (2-party shares)
Recorded Vote: 48.3%, 255 EV
Election Model: Kerry 51.8%, 337 EV (snapshot)
State exit poll aggregate: 51.7%, 337 EV
Unadjusted National Exit poll: Kerry 51.7-Bush 47%
True Vote Model: 53.6%, 364 EV

2008 Election Model
Obama 53.1%, 365.3 EV (simulation mean);
Recorded: 52.9%, 365 EV
State unadjusted exit poll aggregate: 58.0%, 420 EV
Unadjusted National Exit Poll: Obama 61.0-McCain 36.2%
True Vote Model: 58.0%, 420 EV

2012 Election Model
Obama Projected: 51.6% (2-party), 332 EV snapshot; 320.7 expected; 321.6 mean
Adjusted National Exit Poll (recorded): 51.0-47.2%, 332 EV
True Vote Model 56.1%, 391 EV (snapshot); 385 EV (expected)
Unadjusted State Exit Polls: not released
Unadjusted National Exit Poll: not released

 
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Posted by on October 29, 2012 in Uncategorized

 

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Final Forecast: 2012 Presidential True Vote/Election Fraud Model

Final Forecast: 2012 Presidential True Vote/Election Fraud Model

Richard Charnin
Nov 5, 2012

The final 2012 Presidential True Vote/Election Fraud Model exactly forecast Obama’s 332 electoral vote. His projected 51.6% two-party recorded share was close to the actual 51.9%. Obama actually did much better in the True Vote Model forecast (391 EV, 56% two-party). As usual, the systematic fraud factor caused the red-shift. But Obama overcame the fraud, just as he did in 2008.

The 2008 Election Model was also right on the money. It forecast that Obama would have a 53.1% recorded share and 365.3 expected EV. He had 52.9% and 365 EV. But he had 58.0% in the True Vote Model and 420 EV. His 58.0% weighted aggregate share of the unadjusted state exit polls (82,000 respondents) confirmed the True Vote Model. He won the unadjusted National Exit Poll (17,836 respondents) by an astounding 61-37%.

The Presidential True Vote and Monte Carlo Simulation Forecast Model is updated on a daily basis. The election is assumed to be held on the latest poll date.

Final Forecast: 11/06/2012 9am
Obama: 320.7 expected electoral votes; 99.6% win probability (498 of 500 trials).
He had a 332 snapshot EV (actual total).
He led the state poll weighted average by 49.3-46.2% (51.6% 2-party share).
He led 50.4-47.0% in 16 of 18 Battleground states with 184 of 205 EV.

Obama led Romney in the RCP National average: 48.8-48.1%.
Rasmussen and Gallup are Likely Voter (LV) polls which lean to the GOP.
Rasmussen: Romney led 49-48%.
Gallup: Romney led 50-49%. It was 51-46% a week ago.

Obama led in the Rand poll 49.5-46.2% (closely matching the state polls). Unlike the national LV polls, the Rand poll doesn’t eliminate respondents but weights them on a scale of 1-10 (based on voter preference and intention to vote).

The 3% Obama margin increase in the Rand poll over the national LV polls illustrates why the LVs understate Obama’s margin by using the Likely Voter Cutoff Model (LVCM). LV polls are a subset of the registered voter (RV) sample. They always understate the Democratic share. The majority of voters eliminated by the Likely Voter Cutoff Model (LVCM) are Democrats.

The True Vote Model indicates that Obama would have 55.2% of the two-party vote with 371 expected EV in a fraud-free election. Will he be able to overcome the systemic fraud factor?

2012 Presidential True Vote and Monte Carlo Simulation Forecast Model (html)
– The Monte Carlo Electoral Vote Simulation is based on the latest state polls and currently assumes an equal split of undecided voters. The expected electoral vote is the sum of the products of the state win probabilities and corresponding electoral votes.

– The True Vote Model is based on plausible turnout estimates of new and returning 2008 voters and corresponding vote shares.

The model calculates an estimated True Vote forecast for the National aggregate or any state. The calculation is displayed below the input data section. State poll-based national vote shares, electoral vote and probabilities are displayed on the right side of the screen.

2008 True Vote 2012 Vote Pct Obama Romney
Obama 76.2 58.0% 72.4 68.8 54.2% 90% 10%
McCain 53.0 40.3% 50.3 47.8 37.7% 7% 93%
Other. 2.20 1.66% 2.10 1.97 1.6% 50% 50%
DNV ...................8.27 6.5% 59% 41%
Total 131.4 100% 124.8 126.8 100% 56.1% 43.9%
..............True Vote........... 71.1 55.7
............. Recorded Vote....... 51.0% 47.2%
............. Projected 2-party... 51.6% 48.4%
............. Electoral Vote
............. Projected Snapshot.. 332 206
............. 500 Simulation Mean. 321 217
............. Expected True EV.... 385 153
............. EV Win Probability.. 99.8%

This worksheet contains the weekly polling trend analysis.

The polling data is from the Real Clear Politics (RCP) and Electoral-vote.com websites. The simulation uses the latest state polls.

View this 500 election trial simulation electoral vote frequency graph.

1988-2008: 274 State exit polls. An 8% Discrepancy

In the six presidential elections from 1988-2008, the Democrats won the average recorded vote by 48-46%. But they led both state and national exit polls by 52-42%. There were approximately 375,000 respondents in the 274 state polls and 90,000 respondents in the six national polls. Overall, an extremely low margin of error.

1988-2008 Unadjusted State and National Exit Poll Database

The Ultimate Smoking Gun that proves Systemic Election Fraud:
1) The Likely Voter Cutoff Model eliminates newly registered Democrats from the LV sub-sample. Kerry had 57-61% of new voters; Obama had 72%.
2) Exit poll precincts are partially selected based on the previous election recorded vote. 
3) In the 1988-2008 presidential elections, 226 of 274 exit polls red-shifted to the Republicans. Only about 137 would normally be expected to red-shift. The probability is zero.
4) 135 of 274 exit polls exceeded the margin of error. Only 14 (5%) would normally be expected. The probability is ZERO.
5) 131 of the 135 exit polls that exceeded the margin of error red-shifted to the Republicans. The probability is ZERO.
 

No exit polls in 19 states

The National Election Pool (NEP) is a consortium of six corporate media giants which funds the pollster Edison Research to do exit polling in the U.S and abroad. The NEP announced that they would not exit poll in 19 states, 16 of which are universally thought of as being solid RED states. Or are they? 

In 2008, Obama won exit polls in AK, AL, AZ, GA, NE, SD. He came close to winning in TX, KY, SC, TN, MS. These former RED states may have turned PURPLE. View this worksheet in the model. 

The bad news is that the NEP decision to eliminate the polls makes it easier for vote margins to be padded and electoral votes flipped. Without the polls, it is much more difficult to calculate the statistical probabilities of fraud based on exit poll discrepancies. In the 1988-2008 elections, the Democrats led the unadjusted state exit polls by 52-42%, but by just 48-46% in the official recorded vote. This is a mathematically impossible result which proves systemic election fraud.

The good news is that the post-election True Vote Model should find implausible discrepancies in the recorded state and national votes. After all, that is what it was designed to do.

Sensitivity Analysis

The pre-election TVM built in the 2012 Election Model uses alternative scenarios of 2008 voter turnout and defection rates to derive a plausible estimate of the total final share. The returning voter assumptions are based on Obama’s 58% True Vote (a plausible estimate) and his 53% recorded share. The latter scenario results in vote shares that are close to the LV polls.

The sensitivity analysis of alternative turnout and vote share scenarios is an important feature in the model. The model displays the effects of effects of incremental changes in turnout rates and shares of returning voters. The tables display nine scenario combinations of a) Obama and McCain turnout rates and b) Obama/Romney shares of returning Obama and McCain voters. Obama’s vote share, winning margin and popular vote win probability are displayed for each scenario.

Registered and Likely Voters

Historically, RV polls have closely matched the unadjusted exit polls after undecided voters are allocated and have been confirmed by the True Vote Model.

Likely Voter (LV) polls are a subset of Registered Voter polls and are excellent predictors of the recorded vote – which always understate the Democratic True Vote. One month prior to the election, the RV polls are replaced by LVs. An artificial “horse race” develops as the polls invariably tighten.

The Likely Voter Cutoff Model (LVCM) understates the voter turnout of millions of new Democrats, thereby increasing the projected Republican share. Democrats always do better in RV polls than in the LVs. Based on the historical record, the Democratic True Vote share is 4-5% higher than the LV polls indicate. The LVs anticipate the inevitable election fraud reduction in Obama’s estimated 55% True Vote share.

Media pundits and pollsters are paid to project the recorded vote – not the True Vote. The closer they are, the better they look. They never mention the fraud factor which gets them there, but they prepare for it by switching to LV polls.

The disinformation loop is closed when the unadjusted, pristine state and national exit polls are adjusted to match the LV recorded vote prediction.

2004 and 2008 Election Models

The 2004 model matched the unadjusted exit polls. Kerry had 51.7% and 337 electoral votes. But the election was stolen. Kerry had 48.3% recorded. View the 2004 Electoral and popular vote trend

The 2008 model exactly matched Obama’s 365 EV. The National model exactly matched his official recorded 52.9% share; the State model projected 53.1%. His official margin was 9.5 million votes.

Obama had 58.0% in the unadjusted, weighted state exit poll aggregate (83,000 respondents) which exactly matched the post-election True Vote Model. Obama’s 23 million True Vote margin was too big to steal.

The National Exit Poll displayed on mainstream media websites (Fox, CNN, ABC, CBS, NYT, etc.) indicates that Obama had 52.9% – his recorded vote. Unadjusted state and national exit polls are always forced to match the recorded share.

But the media never discussed the fact that Obama had 61% in the unadjusted National Exit Poll (17,836 respondents). View the 2008 Electoral and popular vote trend

This graph summarizes the discrepancies between the 1988-2008 State Exit Polls and the corresponding Recorded Votes.

The True Vote Model

The 2008 True Vote Model (TVM) determined that Obama won in a landslide by 58-40.3%. Based on the historical red-shift, he needs at least a 55% True Vote share to overcome the systemic 5% fraud factor. The TVM was confirmed by the unadjusted state exit poll aggregate: Obama had an identical 58-40.5% margin (83,000 respondents). He won unadjusted National Exit Poll (17,836 respondents) by an even bigger 61-37% margin.

In projecting the national and state vote, a 1.25% annual voter mortality rate is assumed. The TVM uses estimated 2008 voter turnout in 2012 and corresponding 2012 vote shares. The rates are applied to each state in order to derive the national aggregate result.

There are two basic options for estimating returning voters. The default option assumes the unadjusted 2008 exit poll as a basis. The second assumes the recorded vote. It is important to note that the True Vote is never the same as the recorded vote. The 1988-2008 True Vote Model utilizes estimates of previous election returning and new voters and and adjusted state and national exit poll vote shares.

Monte Carlo Simulation

The simulation consists of 500 election trials. The electoral vote win probability is the number of winning election trials divided by 500.

There are two forecast options in the model. The default option uses projections based on the latest pre-election state polls. The second is based on the state True Vote. The fraud factor is the difference between the two.

The projected vote share is the sum of the poll and the undecided voter allocation (UVA). The model uses state vote share projections as input to the Normal Distribution function to determine the state win probability.

In each election trial, a random number (RND) between 0 and 1 is generated for each state and compared to Obama’s state win probability. If RND is greater than the win probability, the Republican wins the state. If RND is less than the win probability, Obama wins the state. The winner of the election trial is the candidate who has at least 270 electoral votes. The process is repeated in 500 election trials.

Electoral Votes and Win Probabilities

The Electoral Vote is calculated in three ways.
1. The Snapshot EV is a simple summation of the electoral votes. It could be misleading if close state elections favor one candidate.
2. The Mean EV is the average of the 500 simulated election trials.
3. The Theoretical EV is the product sum of the state electoral votes and corresponding win probabilities. A simulation or meta-analysis is not required to calculate the expected EV.

The Mean EV approaches the Theoretical EV as the number of election trials increase. This is an illustration of the Law of Large Numbers.

Obama’s electoral vote win probability is his winning percentage of 500 simulated election trials.

The national popular vote win probability is calculated using the national aggregate of the the projected vote shares. The national margin of error is 1-2% lower than the MoE of the individual states. That is, if you believe the Law of Large Numbers and convergence to the mean.

The Fraud Factor

The combination of True Vote Model and state poll-based Monte Carlo Simulation enables an analyst to determine if the forecast electoral and popular vote share estimates are plausible. The aggregate state poll shares can be compared to the default TVM.

The TVM can be forced to match the aggregate poll projection by…
– An incremental change in vote shares. A red flag would be raised if the match required that Obama captured 85% of returning Obama voters and Romney had 95% of returning McCain voters (a 10% net defection).

– Adjusting 2008 voter turnout in 2012. For example, if McCain voter turnout is required to be 10-15% higher than Obama’s, that would raise a red flag.

– Setting the returning voter option to the 2008 recorded vote. The implicit assumption is that the 2008 recorded vote was the True Vote. But the 2008 election was highly fraudulent. Therefore, the model vote shares will closely match the likely voter polls.

Check the simulated, theoretical and snapshot electoral vote projections and corresponding win probabilities.

In 2004, Election Model forecasts were posted weekly using the latest state and national polls. The model was the first to use Monte Carlo simulation and sensitivity analysis to calculate the probability of winning the electoral vote. The final Nov.1 forecast had Kerry winning 337 electoral votes with 51.8% of the two-party vote, closely matching the unadjusted exit polls.

2004 Election Model Graphs

State aggregate poll trend
Electoral vote and win probability
Electoral and popular vote
Undecided voter allocation impact on electoral vote and win probability
National poll trend
Monte Carlo Simulation
Monte Carlo Electoral Vote Histogram

In the 2006 midterms, the adjusted National Exit Poll was forced to match the House 52-46% Democratic margin. But the 120 Generic Poll Trend Model forecast that the Democrats would have a 56.4% share – exactly matching the unadjusted exit poll.

The 2008 Election Model projection exactly matched Obama’s 365 electoral votes and was within 0.2% of his 52.9% recorded share. He won by 9.5 million votes. But the model understated his True Vote. The forecast was based on final likely voter (LV) polls that had Obama leading by 7%. Registered voter (RV) polls had him up by 13% – even before undecided voters were allocated. The landslide was denied.

The post-election True Vote Model determined that Obama won by 23 million votes with 420 EV. His 58% share matched the unadjusted state exit poll aggregate (83,000 respondents).

Exit pollsters and media pundits have never explained the massive 11% state exit poll margin discrepancy or the impossible 17% National Exit Poll discrepancy. If they did, they would surely claim that the discrepancies were due to reluctant Republican responders. But they will not even try to explain the impossible returning voter adjustments required to force the polls to match the recorded vote in the 1988, 1992, 2004 and 2008 elections.

2008 Election Model Graphs
Aggregate state polls and projections (2-party vote shares)
Undecided vote allocation effects on projected vote share and win probability
Obama’s projected electoral vote and win probability
Monte Carlo Simulation Electoral Vote Histogram

Published 10/27/12:
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

Track Record: Election Model Forecast; Post-election True Vote Model
https://docs.google.com/document/d/1zRZkaZQuKTmmd_H0xMAnpvSJlsr3DieqBdwMoztgHJA/edit

2004 Election Model (2-party shares)
Kerry 51.8%, 337 EV (snapshot)
State exit poll aggregate: 51.7%, 337 EV
Recorded Vote: 48.3%, 255 EV
True Vote Model: 53.6%, 364 EV

2008 Election Model
Obama 53.1%, 365.3 EV (simulation mean);
Recorded: 52.9%, 365 EV
State exit poll aggregate: 58.0%, 420 EV
True Vote Model: 58.0%, 420 EV

2012 Election Model
Obama Projected: 51.6% (2-party), 332 EV snapshot; 320.7 expected; 321.6 mean
Adjusted National Exit Poll (recorded): 51.0-47.2%, 332 EV
True Vote Model 56.1%, 391 EV (snapshot); 385 EV (expected)
Unadjusted State Exit Polls: not released
Unadjusted National Exit Poll: not released

 
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Posted by on October 17, 2012 in 2012 Election

 

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9/26/ 2012 Presidential True Vote/Election Fraud Simulation Model:Obama 342 EV; 100% Win Probability

9/26/ 2012 Presidential True Vote/Election Fraud Simulation Model:Obama 342 EV; 100% Win Probability

Richard Charnin
Sept. 26, 2012

Update Note: Click this link to the final 2012 forecast. It was exactly right: Obama had 51.6% (2-party) and 332 EV with a 99.6% win probability. But his True Vote was 55% with 380 EV. https://richardcharnin.wordpress.com/2012/11/07/4380/

The 2008 Election Model also predicted Obama’s recorded vote exactly at 365 EV and 52.9% with a 100% win probability. But his True Vote was 58.0% with 420 EV. http://www.richardcharnin.com/2008ElectionModel.htm

The 2012 Presidential True Vote and Monte Carlo Simulation Forecast Model uses two forecast methods. The Monte Carlo Electoral Vote Simulation is based on the latest state polls. The True Vote Model calculates vote shares based on a feasible estimate of new and returning 2008 voters and corresponding vote shares. The model is updated periodically for the latest state and national polls. The projections assume the election is held on the latest poll date.

Obama increased his expected electoral vote from 320 to 342 by gaining the lead in the North Carolina and Iowa polls. The expected electoral vote is based on the state win probabilities. If the election were held today, the Monte Carlo electoral vote simulation indicates that Obama would have a 100% probability of winning as he won all 500 election simulation trials. But there are six weeks to so.

Obama’s 49.2-44.3% margin in the weighted state pre-election polls is very close to his 48.9-44.9% lead in the RCP national average – a joint confirmation. His lead increased to 50-44% in the Gallup RV tracking poll (2% MoE, 3050 sample).

2004 and 2008 Election Models

The 2004 model matched the unadjusted exit polls. Kerry had 51.7% and 337 electoral votes. But the election was stolen. Kerry had 48.3% recorded. View the 2004 Electoral and popular vote trend

The 2008 model exactly matched Obama’s 365 EV. The national model exactly matched his official recorded 52.9% share; the state model projected 53.1%. His official margin was 9.5 million votes. But Obama had 58.0% in the unadjusted, weighted state exit poll aggregate (83,000 respondents) which exactly matched the True Vote Model. His 23 million vote margin was too big to steal. This is the whopper no one in the media talks about: Obama had 61% in the unadjusted National Exit Poll (17,836 respondents). View the 2008 Electoral and popular vote trend

Forecast Summary

Approximately 7% of voters are undecided and may hold the key to the election. I suspect they are mostly Democrats disillusioned with Obama but scared by Romney and Ryan. The model currently assumes an equal split of the undecided vote. If undecided voters break for Obama, he will be in a commanding position to win re-election.

The Likely Voter (LV) polls anticipate the inevitable election fraud reduction in Obama’s estimated 56.3% True Vote share and 402 electoral votes.

The source of the polling data is the Real Clear Politics (RCP) website. The simulation uses the latest state polls. Recorded 2008 vote shares are used for states which have not yet been polled.


9/26/2012
UVA = undecided voter allocation = 50/50%
True Vote Model Obama Romney
True Vote...... 56.3% 43.7% (see model)
Expected EV.... 402 136 EV = sum(state win prob (i) * EV(i)), i=1,51
Snapshot EV.... 410 128 Sum of state EV
EV Win Prob.... 100% 0%

State Polls
Average........ 49.2% 44.3% (state vote-weighted average)
Projection..... 52.4% 47.6% (RCP Polls + UVA)
Pop. Win Prob.. 94.5% 5.5% (3.0% MoE)
Expected EV.... 342.4 195.6 EV = sum(state win prob(i) * EV(i)), i=1,51
Snapshot EV.... 343 195 Sum of winning state electoral votes

National Polls
Average........ 48.9% 44.9% (RCP poll average)
Projection..... 52.0% 48.0% (RCP polls + UVA)
Pop. Win Prob.. 97.5% 2.5% (2.0% MoE)
Gallup......... 50% 44% (3050 RV sample, 2.0% MoE)
Rasmussen...... 46% 46% (1500 LV sample, 3.0% MoE)

Monte Carlo Simulation (500 Election trials)
Projection..... 52.4% 47.6% (RCP state polls + UVA)
Mean EV........ 341.8 196.2 (average of 500 election trials)
Maximum EV..... 375 163
Minimum EV..... 309 229
EV Win Prob.... 100% 0% (500 wins/500 election trials)

Polling samples are based on prior election recorded votes – not the previous True Vote or unadjusted exit poll. Likely voter (LV) polls discount the pervasive systematic fraud factor. They are traditionally excellent predictors of the recorded vote – which always understate the Democratic True Vote.

In the six presidential elections from 1988-2008, the Democrats won the average recorded vote by 48-46%. But they led both state and national exit polls by 52-42%. There were approximately 375,000 respondents in the 274 state polls and 90,000 respondents in the six national polls. Overall, an extremely low margin of error.

This graph summarizes the discrepancies between the1988-2008 State Exit Polls vs. the corresponding Recorded Votes

Based on the historical record, Obama’s True Vote share is about 4-5% higher than the latest polls indicate. It is a certainty that he will lose millions of votes on Election Day to fraud. The only question is: Will he overcome the systemic fraud factor? As of today, it appears he will.

The 2008 True Vote Model (TVM) determined that Obama won in a landslide by 58-40.3%. Based on the historical red-shift, he needs at least a 55% True Vote share to overcome the systemic 5% fraud factor. The TVM was confirmed by the unadjusted state exit poll aggregate: Obama had an identical 58-40.5% margin (83,000 respondents). He won unadjusted National Exit Poll (17,836 respondents) by an even bigger 61-37% margin.

The National Exit Poll displayed on mainstream media websites (Fox, CNN, ABC, CBS, NYT, etc.) indicate that Obama had 52.9% – his recorded vote. Unadjusted state and national exit polls are always forced to match the recorded share.

The True Vote Model

In projecting the national vote, the required input to the TVM are returning 2008 voter turnout rates in 2012 and estimated 2012 vote shares. The rates are applied to each state in order to derive the national aggregate turnout . A 1.25% annual voter mortality rate is assumed. There are two options for estimating returning voters. The default option assumes that 2008 voters return in proportion to the unadjusted 2008 exit poll aggregate (Obama won by 58-40.5%). In this scenario, Obama wins by 55-45% with 380 EV and has a 100% EV win probability.

It is important to note that the True Vote is never the same as the recorded vote. The 1988-2008 True Vote Model utilizes estimates of previous election returning and new voters and and adjusted state and national exit poll vote shares.

Sensitivity analysis

The TVM displays the effects of effects of incremental changes in turnout rates and shares of returning voters. Three tables are generated consisting of nine scenario combinations of a) Obama and McCain turnout rates and b) the Obama/Romney shares of returning Obama and McCain voters. The output tables display resulting vote shares, vote margins and popular vote win probabilities.

Monte Carlo Simulation: 500 election trials

There are two forecast options in the simulation model. The default option uses projections based on the latest pre-election state polls. The second uses projections based on the state True Vote. The difference between the two approximates the fraud factor.

The projected vote share is the sum of the poll share and the undecided voter allocation (UVA). The model uses state vote share projections as input to the Normal Distribution function to determine the state win probability.

The simulation consists of 500 election trials. The electoral vote win probability is the number of winning election trials divided by 500.

In each election trial, a random number (RND) between 0 and 1 is generated for each state and compared to Obama’s state win probability. If RND is greater than the win probability, the Republican wins the state. If RND is less than the win probability, Obama wins the state. The winner of the election trial is the candidate who has at least 270 electoral votes. The process is repeated in 500 election trials.

2008 State Exit Poll and recorded vote data is displayed in the ‘2008‘ worksheet. The latest state polls are listed in the ‘Trend/Chart” worksheet, The data is displayed graphically in the ‘PollChart’ worksheet. A histogram of the Monte Carlo Simulation (500 trials) is displayed in the ‘ObamaEVChart’ worksheet.

Electoral Votes and Win Probabilities

The Electoral Vote is calculated in three ways.
1. The Snapshot EV is a simple summation of the state electoral votes. It could be misleading since there may be several very close elections which favor one candidate.
2. The Mean EV is the average electoral vote of the 500 simulated elections.
3. The Theoretical (expected) EV is the product sum of all state electoral votes and corresponding win probabilities. A simulation or meta-analysis is not required to calculate the expected EV.

The Mean EV approaches the Theoretical EV as the number of election trials increase. This is an illustration of the Law of Large Numbers.

Obama’s electoral vote win probability is his winning percentage of 500 simulated election trials.

The national popular vote win probability is calculated using the normal distribution using the national aggregate of the the projected vote shares. The national aggregate margin of error is 1-2% lower than the average MoE of the individual states. That is, if you believe the Law of Large Numbers and convergence to the mean.

The Fraud Factor

Election fraud reduced the 1988-2008 Democratic presidential unadjusted exit poll margin from 52-42% to 48-46%. View the 1988-2008 Unadjusted State and National Exit Poll Database

The combination of True Vote Model and state poll-based Monte Carlo Simulation enables the analyst to determine if the electoral and popular vote share estimates are plausible. The aggregate state poll shares can be compared to the default TVM.

The TVM can be forced to match the aggregate poll projection by…
– Adjusting vote shares by an incremental change. A red flag would be raised if the match required, if for example Obama captured 85% of returning Obama voters and Romney had 95% of returning McCain voters (a 10% net defection).

– Adjusting 2008 voter turnout in 2012. For example, if McCain voter turnout is required to be 10-15% higher than Obama’s, that would raise a red flag.

– Setting the returning voter option to the 2008 recorded vote. The implicit assumption is that the 2008 recorded vote was the True Vote. But the 2008 election was highly fraudulent. Therefore, model vote shares will closely match the likely voter polls.

Check the simulated, theoretical and snapshot electoral vote projections and corresponding win probabilities.

Election Model Projections: 2004-2010

In 2004, I created the Election Model , and posted weekly forecasts using the latest state and national polls. The model was the first one to use Monte Carlo simulation and sensitivity analysis to calculate the probability of winning the electoral vote. The final Nov.1 forecast had Kerry winning 337 electoral votes with 51.8% of the two-party vote. The forecast closely matched the unadjusted exit polls.

2004 Election Model Graphs

State aggregate poll trend
Electoral vote and win probability
Electoral and popular vote
Undecided voter allocation impact on electoral vote and win probability
National poll trend
Monte Carlo Simulation
Monte Carlo Electoral Vote Histogram

In 2006, the adjusted National Exit Poll indicated that the Democrats won the House by a 52-46% vote share. But the 120 Generic Poll Forecasting Regression Model indicated that they would have 56.4% – exactly matching the unadjusted exit poll.

The 2008 Election Model projection exactly matched Obama’s 365 electoral votes and was within 0.2% of his 52.9% recorded share. He won by 9.5 million votes. But the model understated his True Vote. The forecast was based on final likely voter (LV) polls that had Obama leading by 7%. Registered voter (RV) polls had him up by 13% – before undecided voter allocation. The landslide was denied. The post-election True Vote Model determined that Obama won by 23 million votes with 420 EV. His 58% share matched the unadjusted state exit poll aggregate (83,000 respondents).

2008 Election Model Graphs

Aggregate state polls and projections (2-party vote shares)
Undecided vote allocation effects on projected vote share and win probability
Obama’s projected electoral vote and win probability
Monte Carlo Simulation Electoral Vote Histogram

Exit pollsters and media pundits have never explained the massive 11% state exit poll margin discrepancy or the impossible 17% National Exit Poll discrepancy. If they did, they would surely claim that the discrepancies were due to reluctant Republican responders. But they will not even try to explain the impossible returning voter adjustments required to force the polls to match the recorded vote in the 1988, 1992, 2004 and 2008 elections.

Pre-election RV and LV Polls

Virtually all early pre-election polls are of Registered Voters (RV). An exception is the Rasmussen poll. It uses the Likely Voter (LV) subset of the full RV sample. Rasmussen is an admitted GOP pollster.

One month prior to the election, pollsters replace the full RV sample polls with LV subsamples. The RV polls are transformed to LVs to promote an artificial “horse race” – and the poll shares invariably tighten. The Likely Voter Cutoff Model (LVCM) effectively understates the turnout of millions of new Democratic voters – and therefore increases the projected Republican share. Democrats always do better in RV polls than in the LVs.

Media pundits and pollsters are paid to project the recorded vote – not the True Vote. And they are usually right. The closer they are, the better they look. They expect there will be fraud, so they prepare the public for it by switching to LV polls which are usually excellent predictors of the recorded vote. But they never mention the fraud factor which gets them there.

Historically, RV polls have closely matched the unadjusted exit polls after undecided voters were allocated< They have been confirmed by the True Vote Model. The loop is closed when unadjusted, pristine state and national exit polls are adjusted to match the LV recorded vote prediction.

In pre-election and exit polls:
1) The Likely Voter Cutoff Model eliminates newly registered Democrats from the LV sub-sample. Kerry had 57-61% of new voters; Obama had 72%.
2) Exit poll precincts are partially selected based on the previous election recorded vote.
3) In the 1988-2008 presidential elections, 226 of 274 exit polls red-shifted" to the Republicans. Only about 137 would normally be expected to red-shift. The probability is zero.
4) 126 of the 274 exit polls exceeded the margin of error. Only 14 (5%) would normally be expected. The probability is ZERO.
5) 123 of the 126 exit polls that exceeded the margin of error red-shifted to the Republicans. The probability is ZERO.

Election Model Forecast; Post-election True Vote Model

2004 (2-party vote shares)
Model: Kerry 51.8%, 337 EV (snapshot)
State exit poll aggregate: 51.7%, 337 EV
Recorded Vote: 48.3%, 255 EV
True Vote Model: 53.6%, 364 EV

2008
Model: Obama 53.1%, 365.3 EV (simulation mean);
Recorded: 52.9%, 365 EV
State exit poll aggregate: 58.0%, 420 EV
True Vote Model: 58.0%, 420 EV

2012 (2-party state exit poll aggregate shares)
Model: Obama 51.6%, 332 EV (Snapshot)
Recorded : 51.6%, 332 EV
True Vote 55.2%, 380 EV

 
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Posted by on September 26, 2012 in 2012 Election

 

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2000-2004 Presidential Elections County True Vote Model

2000-2004 Presidential Elections County True Vote Model

Richard Charnin

March 28, 2012

The database has been restructured for easier use. It is based on county recorded vote changes and 2000 and 2004 as well as National Exit Poll vote shares. It now calculates the approximate 2004 True Vote for counties in 21 states.

The 2004 County True Vote Model:
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDNzZWhMcF9sS3pHRWdUZE8zdEs4aGc#gid=23

In 2000, Gore won the unadjusted state exit polls by 50.8-44.4%. He won the National Exit Poll by 48.5-46.3%

In 2004, Kerry won the unadjusted state exit polls by 51.1-47.6%. He won the National Exit Poll by 51.7-47.0%%

The database contains Election Day recorded votes. In 2000 approximately 2.7 million votes were recorded after Election Day; in 2004 approximately 6 million were. Gore and Kerry each had 55% of the late two-party vote.

In 2000, there were approximately 6 million uncounted votes. In 2004, there were approximately 4 million. Gore and Kerry had 70-80%. Total Votes Cast, which includes uncounted votes, are not available by county and therefore not included in the County True Vote calculations. Therefore, the Democratic County True Vote is conservative (uncounted votes are 70-80% Democratic). Total votes cast are included in the National and State True Vote models.

The number of returning 2000 voters is calculated assuming 5% voter mortality over the four year period. The default turnout assumption is that 98% of living 2000 voters voted in 2004.

The number of new voters is calculated as the difference between the 2004 recorded vote and the number of returning 2000 voters. This is just an approximation since the recorded 2000 county vote is used – not the True Vote based on total votes cast .

The Model uses adjusted 12:22am National Exit Poll vote shares as a basis for calculating total state and county vote shares. The adjusted shares are applied to each county’s estimated share of new voters and returning Gore, Bush and Other voters. The weighted average of the county vote shares should closely match the calculated state True Vote.

State and county vote shares are calculated based on the differential between the unadjusted state and national exit poll shares.

The Input sheet is for data entry. Enter the state code in cell A2.

The default assumption is that 2000 voters return to vote in proportion to the 2000 unadjusted exit poll. Enter code 1 to use the 2000 recorded vote as the returning voter option. Since the unadjusted 2000 exit poll is close to the True Vote, the default option is a better choice.

The user has the option of incrementing the returning Gore voter mix percentage. The Bush share will decrease (increase) by the same percentage.

The living 2000 voter turnout rate is set to 98%, but can be changed if desired.

In order to gauge the impact of changes in vote shares, incremental changes to Kerry’s base case vote shares can be input. Bush’s shares will adjust automatically in the opposite direction (the total must equal 100%). Other third-party vote shares are unchanged.

Analyzing the results
The data is sorted by 2004 county vote. The discrepancies are displayed as vote margin (in thousands) and a percentage. The probability of fraud increases as the discrepancy increases. The county True Vote is only an estimate. It can only be determined if the ballots are hand-counted.

The correlation statistic shows the relationship between two variables and ranges from -1 to +1, where -1 is a perfectly negative correlation and +1 is perfectly positive. A near-zero correlation indicates that there is no relationship. A positive correlation indicates that both variables move in the same direction: as one variable increases (decreases), the other also increases (decreases). A negative correlation indicates just the opposite: as one variable increases (decreases) the other decreases (increases).

The model calculates the correlation statistic (relationship) between Kerry’s recorded vote share and the True Vote discrepancy. In general, there is a strong negative correlation between the variables, indicating that as Obama’s recorded county vote share increases (decreases) the discrepancy decreases (increases). This is an indication that the GOP counties are the most fraudulent (as measured by vote share margin discrepancy).

For example, in Ohio, the -0.82 correlation was very strong indicating that Bush counties were extremely fraudulent relative to Kerry counties (based on vote share margin discrepancies).

County Correlation Ratios between the Democratic Recorded Vote and
the True Vote Share Margin Discrepancy
State 2004 2008
NC -0.01 -0.72
WI -0.70 -0.50
OH -0.82 -0.50
NY -0.62 -0.45
FL -0.43 -0.79

Florida
At 8:40pm CNN showed that of 2846 exit polled, Bush led by 49.8-49.7%.
Kerry won the unadjusted exit poll (2862 respondents) by 50.8-48.0%.
But at 1:41am, the poll flipped to Bush (52.1-47.9%) for the SAME 2862 RESPONDENTS, matching the recorded vote a 381,000 vote margin.
Kerry won the True Vote by 52.7-46.1%, a 500,000 vote margin.

Kerry’s largest discrepancies from the True Vote were in DRE counties:
Broward, Hillsborough, Palm Beach, Dade, Pinellas.
Most fraudulent counties based on…
Votes: Dade Broward Palm Beach
Margin: Broward Palm Beach Volusia Polk

Ohio
At 7:30pm CNN showed that of 1963 exit polled, Kerry led by 52.1-47.9%
Kerry won the unadjusted exit poll (2020 respondents) by 54.1-45.9%.
At 1:41am, the poll flipped to Bush (50.9-48.6%) for the SAME 2020 RESPONDENTS, matching the recorded vote, a 119,000 vote margin.
Kerry won the True Vote by 53.1-45.5%, a 426,000 vote margin.

Ohio used Punched card machines, DREs and Optical Scanners.
Most fraudulent counties based on…
Votes: Cuyahoga Franklin Montgomery Butler
Margin: Butler Warren Clermont

New York
All counties Lever machines.
Kerry won the recorded vote by 58.4-40.1%, a 1,251,000 vote margin.
Kerry won the Exit Poll by 62.1-36.2%.
Kerry won the True Vote by 63.0-35.1%, a 2,060,000 vote margin.
Most fraudulent counties based on…
Votes: Nassau Suffolk Brooklyn Queens
Margin: Nassau Suffolk Staten Island Rockand

Wisconsin
Kerry won the recorded vote by 49.7-49.3%, an 11,000 vote margin.
Kerry won the Exit Poll by 52.0-46.8%.
Kerry won the True Vote by 52.8-45.6%, a 217,000 vote margin.
Most fraudulent counties based on…
Votes: Waukesha Brown Sheboygan
Margin: Waukesha Brown Sheboygan Washington

Arizona
In 2000 Gore won the exit poll (47.2-46.4%) but lost the vote by 50.9-44.7%.
In 2004, Bush won the exit poll (52.8-46.3%) and the recorded vote (54.9-44.4%).

But Kerry won the True Vote by 52.0-46.2% (assuming 2000 voters returned in proportion to the 2000 exit poll). If the model is correct, there was massive election fraud (a 16% discrepancy).

Pennsylvania
Most fraudulent counties based on…
Votes: Allegheny Montgomery Bucks
Margin: Northampton York Westmoreland

 

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