# Category Archives: True Vote Models

## Historical Overview of Election Fraud Analysis

Richard Charnin
Jan.31, 2013

http://richardcharnin.com/

Historical Overview

I have written two books on election fraud which prove that the official recorded vote has deviated from the True Vote in every election since 1968 – always favoring the Republicans. Voting machine “glitches” are not due to machine failures; they are caused by malicious programming.

In the 1968-2012 Presidential elections, the Republicans won the average recorded vote by 48.7-45.8%. The 1968-2012 National True Vote Model (TVM) indicates the Democrats won the True Vote by 49.6-45.0% – a 7.5% margin discrepancy.

In the 1988-2008 elections, the Democrats won the unadjusted state exit poll aggregate by 52-42% – but won the recorded vote by just 48-46%, an 8% margin discrepancy. The state exit poll margin of error was exceeded in 126 of 274 state presidential elections from 1988-2008. The probability of the occurrence is ZERO. Only 14 (5%) would be expected to exceed the MoE at the 95% confidence level. Of the 126 which exceeded the MoE, 123 red-shifted to the Republican. The probability P of that anomaly is ABSOLUTE ZERO (5E-106). That is scientific notation for

P= .000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000005.

The proof is in the 1988-2008 Unadjusted State Exit Polls Statistical Reference. Not one political scientist, pollster, statistician, mathematician or media pundit has ever rebutted the data or the calculation itself. They have chosen not to discuss the topic. And who can blame them? Job security is everything.

Election forecasters, academics, political scientists and main stream media pundits never discuss or analyze the statistical evidence that proves election fraud is systemic – beyond a reasonable doubt. This site contains a compilation of presidential, congressional and senate election analyses based on pre-election polls, unadjusted exit polls and associated True Vote Models. Those who never discuss or analyze Election Fraud should focus on the factual statistical data and run the models. If anyone wants to refute the analytic evidence, they are encouraged to do so in a response. Election forecasters, academics and political scientists are welcome to peer review the content.

The bedrock of the evidence derives from this undisputed fact: National and state actual exit poll results are always adjusted in order to force a match to the recorded vote – even if doing so requires an impossible turnout of prior election voters and implausible vote shares.

All demographic categories are adjusted to conform to the recorded vote. To use these forced final exit polls as the basis for election research is unscientific and irresponsible. The research is based on the bogus premise that the recorded vote is sacrosanct and represents how people actually voted. Nothing can be further from the truth.

It is often stated that exit polls were very accurate in elections prior to 2004 but have deviated sharply from the recorded vote since. That is a misconception. UNADJUSTED exit polls have ALWAYS been accurate; they closely matched the True Vote Model in the 1988-2008 presidential elections. The adjusted, published exit polls have always matched the fraudulent RECORDED vote because they have been forced to. That’s why they APPEAR to have been accurate.

The Census Bureau indicates that since 1968 approximately 80 million more votes were cast than recorded. And these were just the uncounted votes. What about the votes switched on unverifiable voting machines and central tabulators? But vote miscounts are only part of the story. The True Vote analysis does not include the millions of potential voters who were illegally disenfranchised and never got to vote.

In 1988, Bush defeated Dukakis by 7 million recorded votes. But approximately 11 million ballots (75% Democratic) were uncounted. Dukakis won the unadjusted exit polls in 24 battleground states by 51-47% and the unadjusted National Exit Poll by 50-49%. The Collier brothers classic book Votescam provided evidence that the voting machines were rigged for Bush.

In 1992, Clinton defeated Bush by 5.8 million recorded votes (43.0-37.5%). Approximately 9 million were uncounted. The National Exit Poll was forced to match the recorded vote with an impossible 119% turnout of living 1988 Bush voters in 1992. The unadjusted state exit polls had Clinton winning a 16 million vote landslide (47.6-31.7%). The True Vote Model indicates that Clinton won by 51-30% with 19% voting for third party candidate Ross Perot.

In 1996, Clinton defeated Dole by 8.6 million recorded votes (49.3-40.7%); 9 million were uncounted. The unadjusted state exit polls (70,000 respondents) had Clinton winning a 16 million vote landslide (52.6-37.1%). The True Vote Model indicates that Clinton had 53.6%.

In 2000, Al Gore won by 540,000 recorded votes (48.4-47.9%). But the unadjusted state exit polls (58,000 respondents) indicated that he won by 50.8-44.4%, a 6 million vote margin. There were nearly 6 million uncounted votes. The True Vote Model had him winning by 51.5-44.7%. But the Supreme Court awarded the election to Bush (271-267 EV). In Florida, 185,000 ballots were uncounted. The following states flipped from Gore in the exit poll to Bush in the recorded vote: AL AR AZ CO FL GA MO NC TN TX VA. Gore would have won the election if he captured just one of the states. Democracy died in this election.

In July 2004 I began posting weekly Election Model projections based on the 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 projection had Kerry winning 337 electoral votes and 51.8% of the two-party vote, closely matching the unadjusted exit polls.

The adjusted 2004 National Exit Poll was mathematically impossible since it indicated that there were 52.6 million returning Bush 2000 voters. But Bush had just 50.5 million recorded votes in 2000 – and only 48 million were alive in 2004. Approximately 46 million voted, therefore the adjusted Final NEP overstated the number of returning Bush voters by 6.5 million. In order to match the recorded vote, the NEP required an impossible 110% living Bush 2000 voter turnout in 2004.

The post-election True Vote Model calculated a feasible turnout of living 2000 voters based on Census total votes cast (recorded plus net uncounted), a 1.25% annual mortality rate and 98% Gore/Bush voter turnout. It determined that Kerry won by 67-57 million and had 379 EV. But Kerry’s unadjusted state exit poll aggregate 51.0% share understated his True Vote Model. There was further confirmation of a Kerry landslide.

Consider the Final National Exit Poll adjustments made to Bush’s approval rating and Party–ID crosstabs.

Bush had a 48% national approval rating in the final 11 pre-election polls. But the Final adjusted National Exit Poll indicated that he had a 53% approval rating – even it was 50% in the unadjusted state exit poll weighted aggregate. Given the 3% differential between the Final NEP and state exit poll ratings, let’s deduct 3% from his 48% pre-election approval. This gives Bush a 45% vote share – a virtual match to the True Vote Model. The exit pollsters had to inflate Bush’s final pre-election 48% average rating by 5% in the NEP in order to have it match the recorded vote – and perpetuate the fraud. There was a near-perfect 0.99 correlation ratio between Bush‘s state approval and unadjusted exit poll share.

Similarly, the unadjusted state exit poll Democratic/Republican Party ID split was 38.8-35.1%. In order to force the National Exit Poll to match the recorded vote, they needed to indicate a bogus 37-37% split.

The correlation between state Republican Party ID and the Bush unadjusted shares was a near-perfect 0.93. This chart displays the state unadjusted Bush exit poll share, approval ratings and Party-ID.

The Final 2006 National Exit Poll indicated that the Democrats had a 52-46% vote share. The Generic Poll Trend Forecasting Model projected that the Democrats would capture 56.43% of the vote. It was within 0.06% of the unadjusted exit poll.

In the 2008 Primaries, Obama did significantly better than his recorded vote.

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

The Final 2008 National Exit Poll was forced to match the recorded vote by indicating an impossible 103% turnout of living Bush 2004 voters and 12 million more returning Bush than Kerry voters. Given Kerry’s 5% unadjusted 2004 exit poll and 8% True Vote margin, one would expect 7 million more returning Kerry than Bush voters – a 19 million discrepancy from the Final 2008 NEP. Another anomaly: The Final 2008 NEP indicated there were 5 million returning third party voters – but only 1.2 million were recorded in 2004. Either the 2008 NEP or the 2004 recorded third-party vote share (or both) was wrong. The True Vote Model determined that Obama won by over 22 million votes with 420 EV. His 58% share was within 0.1% of the unadjusted state exit poll aggregate (83,000 respondents).

In the 2010 Midterms the statistical evidence indicates that many elections for House, Senate, and Governor, were stolen. The Wisconsin True Vote Model contains worksheets for Supreme Court and Recall elections. A serious analyst can run them and see why it is likely that they were stolen.

In 2012, Obama won the recorded vote by 51.0-47.2% (5.0 million vote margin) and once again overcame the built-in 5% fraud factor. The 2012 Presidential True Vote and Election Fraud Simulation Model exactly forecast Obama’s 332 electoral vote based on the state pre-election polls. The built-in True Vote Model projected that Obama would win by 56-42% with 391 electoral votes. But just 31 states were exit polled, therefore a comparison between the True Vote Model and the (still unreleased) state and national unadjusted exit polls (i.e. the red-shift) is not possible. Obama won the 11.7 million Late votes recorded after Election Day by 58-38%. In 2008, he won the 10.2 million late votes by 59-37%. The slight 2% margin difference is a powerful indicator that if a full set of 2012 unajusted state and national exit polls were available, they would most likely show that Obama had 55-56% True Vote share.

## 1968-2012 Presidential Election Fraud: An Interactive True Vote Model Proof

1968-2012 Presidential Election Fraud: An Interactive True Vote Model Proof

http://richardcharnin.com/

Richard Charnin
Jan. 22,2013

The 1968-2012 National True Vote Model (TVM) has been updated to include the 2012 election. Anyone can run the model and calculate the True Vote for every presidential election since 1968. Only two inputs are required: the election year and the calculation method (1-5). These deceptively simple inputs produce a wealth of information and insight.

In the 1968-2012 elections, the Republicans led the average recorded vote 48.7-45.8%. The Democrats led the True Vote by 49.6-45.1%, a 7.4% margin discrepancy.

The calculation methods are straightforward. Method 1 reproduces the Final National Exit Poll which is always adjusted to match the official recorded vote. It is a mathematical matrix of deceit. Consider the impossible turnout of previous election Republican voters required to match the recorded vote in 1972 (113%), 1988 (103%), 1992 (119%), 2004 (110%) and 2008 (103%). This recurring anomaly is a major smoking gun of massive election fraud.

Methods 2-5 calculate the vote shares based on feasible returning voter assumptions. There are no arbitrary adjustments. Method 2 assumes returning voters based on the previous election recorded vote; method 3 on total votes cast (includes uncounted votes); method 4 on the unadjusted exit poll; method 5 on the previous (calculated) True Vote.

In the 12 elections since 1968, there have been over 80 million net (of stuffed) uncounted ballots, of which the vast majority were Democratic. And of course, the advent of unverifiable voting machines provides a mechanism for switching votes electronically.

Final election vote shares are dependent on just two factors: voter turnout (measured as a percentage of previous living election voters) and voter preference (measured as percentage of new and returning voters).

The TVM uses best estimates of returning voter turnout (“mix”). The vote shares are the adjusted National Exit Poll shares that were applied to match the recorded vote.

It turns out that the Final Exit Poll match to the recorded vote is primarily accomplished by changing the returning voter mix to overweight Republicans.

In 2004, the adjusted National Exit Poll indicated that 43% of voters were returning Bush 2000 voters (implying an impossible 110% Bush 2000 voter turnout in 2004) and 37% were returning Gore voters. But just changing the returning voter mix was not sufficient to force a match to the recorded vote; the Bush shares of returning and new voters had to be inflated as well. Kerry won the unadjusted NEP (13660 respondents) by 51.0-47.5%.

In 2008, the adjusted NEP indicated that 46% of voters were returning Bush voters (an impossible 103% turnout) and 37% returning Kerry voters. Obama won the unadjusted NEP (17836 respondents) by 61.0-37.5%.

Sensitivity Analysis

The final NEP shares of new and returning voters are best estimates based on total votes cast in the prior and current elections and a 1.25% annual mortality rate. But we need to gauge the effect of incremental changes in the vote shares on the bottom line Total Vote. The TVM does this automatically by calculating a True Vote Matrix of Plausibility (25 scenarios of alternative vote shares and corresponding vote margins).

The base case turnout percentage of prior election voters is assumed to be equal for the Democrat and Republican. The turnout sensitivity analysis table displays vote shares for 25 combinations of returning Democratic and Republican turnout rates using the base case vote shares.

The National Election Pool consists of six media giants and funds the exit polls. In 2012 the NEP decided to poll in just 31 states, claiming that it would save them money in these “tough” times. It would have cost perhaps \$5 million to poll the other 19 states. Split it six ways and it’s less than the salary of a media pundit.

The published 2012 National Exit Poll does not include the “Voted in 2008” crosstab. It would have been helpful, but we don’t really need it. We calculated the vote shares required to match the recorded vote by trial and error, given the 2008 recorded vote as a basis. After all, that’s what they always do anyway.

Posted by on January 24, 2013 in True Vote Models, Uncategorized

## 2012 Election Fraud: A True Vote Model Proof

2012 Election Fraud: A True Vote Model Proof

Richard Charnin
Jan. 2, 2013

This 2012 True Vote Model analysis will show that Obama overcame the systemic, built-in 4-5% red-shift fraud factor. He won by an official 51.0-47.2%, a 5.0 million margin. But he had an approximate 55-43% True Vote, a 15.5 million margin.

Media Gospel
An objective analysis shows that Obama must have done much better than his recorded margin. 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 biased. So they adjust exit poll weights and vote shares to match the sacrosanct recorded vote. They never consider the possibility that their samples were good and the elections were fraudulent.

Two Possibilities
Either election fraud is systemic or elections are fair. Those still not convinced by the overwhelming statistical and factual evidence and maintain that election fraud is just a conspiracy theory are welcome to try and refute the following analysis.

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 2008 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% True Vote 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 is systemic, but 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 analysis 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 has always been asked in prior exit polls. 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.

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 do a sensitivity analysis of alternative turnout and vote share scenarios. Is it because they have never considered this powerful modeling tool? Or is it because they know it would produce results that they would rather not talk about?

The 2012 True Vote Model Base Case assumptions were as follows:
1. Obama won the 2008 True Vote: 58%-40.3%
2. Obama and McCain 2008 voters turned out at a 95% rate in 2012
3. Obama had 90% of returning Obama voters and 7% of McCain
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 share assumptions, Romney needed an implausibly low 72% turnout of Obama 2008 voters and 95% turnout of McCain voters in order to match the recorded vote.

2008 National Exit Poll
To put the 2012 True Vote Model 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. But to force a match to the recorded vote (Obama by 52.9-45.6%), the poll indicated that 46% (60.3 million) of the 2008 electorate were returning Bush voters and just 37% (48.6 million) were returning Kerry voters. This is an impossibility; it implies that 103% of living Bush 2004 voters returned to vote in 2008.

On the other hand, assuming Kerry won the True Vote by 53.7-45.3%, the returning 2004 voter mix is a feasible Kerry 47.5/Bush 40.0% and Obama won the True Vote by 58.0-40.3%.

The Late Vote – a True Vote Confirmation
The recurring pattern of the Democratic presidential late vote share exceeding the Election Day share by approximately 7% is additional confirmation of fraud. In 2012, Obama led 50.3-48.1% in the 117.4 million votes recorded on Election Day. But he had a whopping 58.0-38.3% margin in the final 11.7 million late recorded votes (129.1 million total). 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 also 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 polls; the 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 national late vote is representative of the national 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 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.

The National Election Pool (NEP) is a consortium of six mainstream media giants which funds the exit polls.
-  Just 31 states were polled. This effectively prevents the calculation of the total aggregate vote share.
- Unadjusted state and national exit polls are not available.
- The How Voted in 2008 category crosstab is not included in the adjusted National Exit Poll displayed on media election websites. It  was a key tool in proving election fraud. In order to match the recorded vote in 1988, 1992, 2004 and 2008, the pollsters needed millions more returning Bush voters from the prior election than were alive.

Why does the NEP place such onerous restrictions on transparency?  It’s bad enough that analysts never get to see the actual, raw precinct exit poll data. What are the NEP and the exit pollsters hiding? If the data prove that fraud was non-existent, it would have been released. But every election has been fraudulent. Even without releasing the precinct data, unadjusted state and national exit polls prove that election fraud is systemic.

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 50% in the unadjusted state exit poll aggregate. The rating was adjusted to 53% in the NEP 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%

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

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

## Election Fraud: An Introduction to Exit Poll Probability Analysis

Richard Charnin
June 23, 2012
Updated: July 5

In any statistical study, the best data must first be collected. The following election fraud analysis is based on the 1988-2008 Unadjusted State and National Exit Poll Spreadsheet Database.

The data source is the Roper Center Public Opinion Archives. Exit polls are available for 274 state presidential electins, 50 in each of the 1992-2008 elections and 24 in 1988.

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

Exit polls are surveys conducted in selected voting precincts that are chosen to represent the overall state voting population demographic. Voters are randomly selected as they leave the precinct polling booth and asked to complete a survey form indicating 1) who they just voted for, 2) how they voted in the previous election, 3) income range, 4) age group, 5) party-id (Democrat, Republican, Independent), 6) philosophy (liberal, moderate, conservative), and many other questions.

In this analysis we consider the most important question: who did you vote for? Having this information, we calculate the discrepancy between the state exit poll and the recorded vote count.

Note that respondents are not asked to provide personal information. There is no excuse for not releasing exit poll/voting results for each of the 1400+ exit poll precincts. There is no privacy issue.

Key results

- Republican presidential vote shares exceeded the corresponding unadjusted exit poll shares in 226 (82.4%) of the 274 state elections for which there is exit poll data. The probability that 226 would red-shift to the Republicans is ZERO. One would normally expect that approximately 137 would shift to the Republicans and 137 to the Democrats.

- Of the 274, there were 55 state elections in which Republicans won the vote and the Democrats won the exit poll. Conversely, the Republicans lost only two elections (Iowa and Minnesota in 2000) in which they won the exit poll. The probability of this occurrence is virtually ZERO. If the elections were fair, the number of flips would be nearly equal.

- The exit poll margin of error (described below) was exceeded in 126 (46%) of the 274 polls. The probability is ZERO. The statistical expectation is that the margin of error (MoE) would be exceeded in 14 polls (5%).

- 123 of the 126 exit polls in which the MoE was exceeded moved to the recorded vote in favor of the Republican (“red shift”). Just 3 moved in favor of the Democrat (“blue shift”). There is a ZERO probability that the one-sided shift was due to chance. It is powerful evidence beyond any doubt of pervasive systemic election fraud.

The Ultimate Smoking Gun that proves Systemic Election Fraud:

Basic Statistics and the True Vote Model
The True Vote Model (TVM) is based on current and previous election votes cast (Census), voter mortality and returning voter turnout. Published National Exit Poll (NEP) vote shares were applied to new and returning voters. The TVM closely matched the corresponding unadjusted exit polls in each election. It shows that the exit poll discrepancies were primarily due to implausible and/or impossible adjustments required to force the NEP to match the recorded vote. The exit polls were forced to match the recorded votes by adjusting the implied number of returning voters from the previous election. These adjustments are clearly indicated by the percentage mix of returning voters in the current election..

The bedrock of statistical polling analysis is the Law of Large Numbers. As the number of observations in a survey increases, the average will approach the theoretical mean value. For instance, in coin flipping, as the number of flips increase, the average percentage of heads will approach the theoretical 50% mean value.

The Normal distribution is considered the most prominent probability distribution in statistics (“the bell curve”). It is used throughout statistics, natural sciences, and social sciences as a simple model for complex phenomena. For example, the observational error in an election polling is usually assumed to follow a normal distribution, and uncertainty is computed using this assumption. Note that a normally-distributed variable has a symmetric distribution about its mean.

The Binomial distribution distribution calculates the probability P that a given number of events (successes) would occur in n trials given that each trial has a constant probability p of success. For instance, the probability of flipping heads (a success) is 50%. In a fair election, the probability that the exit poll would flip from the Democrat to the Republican is also 50%.

The Poisson distribution calculates the probability of a series of events in which each event has a very low probability. For instance, there is a 5% (1 in 20) probability that the recorded vote share will differ from the exit poll beyond the MoE.

The Binomial distribution converges towards the Poisson as the number of trials (n) approaches infinity while the product (np) remains fixed (p is the probability). Therefore the Poisson distribution with parameter λ = np can be used as an approximation to the Binomial distribution B(n,p) if n is sufficiently large and p sufficiently small.

The exit poll margin of error is based on the number of respondents and the “cluster effect” (assumed as 0.30). The Margin of Error Calculator illustrates the effects of sample size and poll share on the margin of error and corresponding win probability.

Ohio 2004 presidential election
Bush won the recorded vote by 50.8-48.7% (119,000 vote margin). In the exit poll, 2020 voters were sampled, of whom 1092 voted for Kerry (54.1%) and 924 for Bush (45.7%). There was a 10.6% discrepancy in margin between the poll and the vote. Given the exit poll result, we can calculate the probability that a) Kerry won the election and b) of Bush getting his recorded vote share.

The Ohio exit poll MoE was 2.8%, so there was a 95.4% probability that the True Vote was within 2.8% of Kerry’s 54.1% exit poll share. The probabilities are a) 95.4% that Kerry’s share was between 51.3% and 56.9% and b) 97.5% that Kerry had at least 51.3%. The Normal distribution calculates the probability P that Kerry won Ohio.
P = 99.8% = Normdist (.541,.500,.028/1.96, true)

Bush won Ohio with a 50.8% recorded share – a 5.1% increase (red-shift) over his 45.7% exit poll share. The probability that the 5.1% shift was due to chance is 1 in 4852 (.02%). So which most closely represented how the True Vote: the exit poll or the recorded vote?

1988 presidential election
As indicated above, 24 state exit polls are listed for 1988 on the Roper Center site. These states accounted for 68.7 million (75%) of the 91.6 million national recorded votes. Dukakis led the 24-poll aggregate 51.6-47.3%, but Bush won the corresponding recorded vote by 52.3-46.8%, a 9.8% discrepancy. The exit poll margin of error was exceeded in 11 of the 24 states – all in favor of Bush (see the summary statistics below).

Dukakis also won the unadjusted National Exit Poll by 49.8-49.2% – but Bush won by 7 million votes, 53.4-45.6%. According to the U.S. Census, 102.2 million votes were cast and 91.6 million recorded, therefore a minimum of 10.6 million ballots were uncounted. Dukakis had approximately 8 million (75%) of the uncounted votes (see below). Of course, voters whose ballots were uncounted were interviewed by the exit pollsters. That may be one of the reasons why Dukakis won the state and national exit polls and lost the recorded vote.

Calculating the probabilities
Given the state recorded vote, exit poll and margin of error for each of 274 elections, we can calculate the probability of the red shift.

The probability P that 55 of 57 exit polls would flip from the Democrats leading in the exit polls to the Republicans winning the recorded vote is given by the Binomial distribution: P= 1-Binomdist(54,57,.5,true)
P= 1.13E-14 = 0.000000000000011 or 1 in 88 trillion!

The probability that the exit poll margin of error would be exceeded in any given state is 5% or 1 in 20. Therefore, approximately 14 of the 274 exit polls would be expected to exceed the margin of error, 7 for the Republican and 7 for the Democrat.

The Republicans did better in the recorded vote than in the exit polls in 226 (82.4%) of the 274 elections. The probability of this one-sided red-shift is 3.7E-31 or 1 in 2.7 million trillion trillion.

The MoE was exceeded in 123 exit polls in favor of the Republican – and just 3 for the Democrat. The simple Poisson spreadsheet function calculates the probability P:
P = 5E-106 = Poisson (123, .025*274, false)
P = 1 in 1.8 billion trillion trillion trillion trillion trillion trillion trillion trillion.
The probability is ZERO. There are 106 places to the right of the decimal!
```P = .0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 000005 ```Sensitivity Analysis
Sensitivity analysis is an important tool for viewing the effects of alternative assumptions on key results from a mathematical model.

In pre-election polls, the margin of error (MoE) is based strictly on the number of respondents. In exit polls, however, a “cluster factor” is added to the calculated MoE. Therefore, the number of states in which the MoE was exceeded in 1988-2008 (and the corresponding probabilities) is a function of the cluster effect.

The MoE was exceeded in 126 of 274 exit polls assuming a 30% “cluster factor” (the base case). Although 30% is the most common estimate, political scientists and statisticians may differ on the appropriate cluster factor to be used in a given exit poll. Therefore, a sensitivity analysis worksheet of various cluster factor assumptions (ranging from 0% to 200%) is displayed in the 1988-2008 Unadjusted Exit Poll Spreadsheet Reference. The purpose is to determine the number of exit polls in which the MoE was exceeded over a range of cluster factors.

If there was no cluster effect, the margin of error was exceeded in 157 of 274 exit polls. In the base case (30% cluster), 126 exceeded the MoE.

Note: MoE is the average margin of error for the 6 elections, CF is the cluster factor, N is the number of exit polls in which the MoE was exceeded.
```MoE CF...N..Probability 2.5% 0% 157 2.0E-106 ZERO 3.2% 30% 126 8.0E-75 ZERO (base case cluster factor) 3.7% 50% 113 1.4E-62 ZERO 5.0% 100% 76 1.5E-31 ZERO (1 in 7 million trillion trillion) 6.2% 150% 50 2.5E-14 (1 in 40 trillion) 7.0% 180% 35 6.6E-7 ( 1 in 1.5 million) 7.5% 200% 25 1.9E-03 (1 in 500) ```
Even with extremely conservative cluster factor assumptions, the sensitivity analysis indicates a ZERO probability that the margin of error would be exceeded in the six elections. Were the massive discrepancies due to inferior polling by the most experienced mainstream media exit pollsters in the world? Or are they further mathematical confirmation of systemic election fraud – beyond any doubt?

Overwhelming Evidence
The one-sided results of the 375,000 state exit poll respondents over the last six presidential elections leads to only one conclusion: the massive exit poll discrepancies cannot be due to faulty polling and is overwhelming evidence that systemic election fraud has favored the Republicans in every election since 1988.

Fraud certainly cost the Democrats at least two elections (2000, 2004) and likely a third (1988). And in the three elections they won, their margin was reduced significantly by election fraud.

To those who say that quoting these impossible probabilities invites derision, that it is overkill, my response is simply this: those are the actual results that the mathematical functions produced based on public data. The mathematical probabilities need to be an integral part of any election discussion or debate and need to be addressed by media pundits and academics.

Media polling pollsters, pundits and academics need to do a comparable scientific analysis of historical exit polls and create their own True Vote models. So-called independent journalists need to discuss the devil in the details of systemic election fraud. They can start by trying to debunk the analysis presented here.

Presidential Summary
``` Election.. 1988 1992 1996 2000 2004 2008 Average Recorded Vote Democrat.. 45.7 43.0 49.3 48.4 48.3 52.9 47.9 Republican 53.4 37.4 40.7 47.9 50.7 45.6 46.0```

``` Unadjusted Aggregate State Exit Polls (weighted by voting population) Democrat.. 50.3 47.6 52.6 50.8 51.1 58.0 51.7 Republican 48.7 31.7 37.1 44.4 47.5 40.3 41.6 ```

```Unadjusted National Exit Poll Democrat.. 49.8 46.3 52.6 48.5 51.7 61.0 51.7 Republican 49.2 33.5 37.1 46.3 47.0 37.2 41.7 ```

1988-2008 Red-shift Summary (274 exit polls)
The following table lists the
a) Number of states in which the exit poll red-shifted to the Republican,
b) Number of states which red-shifted beyond the margin of error,
c) Probability of n states red-shifting beyond the MoE,
d) Democratic unadjusted aggregate state exit poll share,
e) Democratic recorded share,
f) Difference between Democratic exit poll and recorded share.
``` Year RS >MoE Probability.... Exit Vote Diff 1988* 20. 11... 5.0E-11..... 50.3 45.7 4.6 Dukakis may have won 1992 44.. 26... 2.4E-25..... 47.6 43.0 4.6 Clinton landslide 1996 43.. 16... 4.9E-13..... 52.6 49.3 3.3 Clinton landslide 2000 34.. 12... 8.7E-09..... 50.8 48.4 2.4 Gore win stolen 2004 40.. 22... 3.5E-20..... 51.1 48.3 2.8 Kerry landslide stolen 2008 45.. 36... 2.4E-37..... 58.0 52.9 5.1 Obama landslide denied Total 226. 123. 5.0E-106.... 51.7 47.9 3.8 * 274 exit polls (24 in 1988, 50 in each of the 1992-2008 elections) ```

The Democrats led the 1988-2008 vote shares as measured by:
1) Recorded vote: 47.9-45.9%
2) Exit Pollster (WPE/IMS): 50.8-43.1%
3) Unadjusted State Exit Polls: 51.7-41.6%
4) Unadjusted National Exit Poll: 51.6-41.7%

True Vote Model (method based on previous election returning voters)
5) Method 1: 50.2-43.4% (recorded vote)
6) Method 2: 51.6-42.0% (allocation of uncounted votes)
7) Method 3: 52.5-41.1% (unadjusted exit poll)
8) Method 4: 53.0-40.6% (recursive True Vote)

The Democrats won the exit poll but lost the recorded vote in the following states. The corresponding decline in electoral votes cost the Democrats to lose the 1988, 2000, 2004 elections:

1988 (7): CA IL MD MI NM PA VT
Dukakis’ electoral vote was reduced from 271 in the exit polls to 112 in the recorded vote. The U.S. Vote Census indicated that there were 10.6 million net uncounted votes in 1988. Since only 24 states were exit polled, a proxy equivalent was estimated for each of the other 26 states by allocating 75% of the uncounted votes to Dukakis. The average 3.47% MoE of the 24 exit polls was assumed for each of the 26 states. Four of the 26 flipped to Bush: CO LA MT SD.

The rationale for deriving the estimate is Method 2 of the 1988-2008 True Vote Model in which 75% of uncounted votes were allocated to the Democrat. The resulting 51.6% average Democratic share (see above) exactly matched the unadjusted exit polls (TVM #3). This article by Bob Fitrakis provides evidence that uncounted votes are heavily Democratic.

1992 (10): AK AL AZ FL IN MS NC OK TX VA
Clinton’s EV flipped from from 501 to 370.

1996 (11): AL CO GA IN MS MT NC ND SC SD VA
Clinton’s EV flipped from 464 to 379.

2000 (12):AL AR AZ CO FL GA MO NC NV TN TX VA (Gore needed just ONE to win)
Gore’s EV flipped from 382 to 267.

2004 (8): CO FL IA MO NM NV OH VA (Kerry would have won if he carried FL or OH)
Kerry’s EV flipped from 349 to 252.

2008 (7): AL AK AZ GA MO MT NE
Obama’s EV flipped from 419 to 365.

Take the Election Fraud Quiz.

Election Model Forecast; Post-election True Vote Model

This is a summary of 2004-2012 pre-election projections and corresponding recorded votes, exit polls and True Vote Models.

2004 Election Model
Kerry Projected 51.8% (2-party), 337 EV (simulation mean)
State exit poll aggregate: 51.1-47.6%, 337 EV
National Exit Poll: 51.7-47.0%
Adjusted National Exit Poll (recorded vote): 48.3-50.7%, 255 EV
True Vote Model: 53.6-45.1%, 364 EV

2006 Midterms
Democratic Generic 120-Poll Trend Model: 56.4-41.6%
Wikipedia recorded vote: 57.7-41.8%
Adjusted Final National Exit Poll (recorded vote): 52.2-45.9%

2008 Election Model
Obama Projected: 53.1-44.9%, 365.3 expected EV; 365.8 EV (simulation mean)
State exit poll aggregate: 58.1-40.3%, 420 EV
National Exit Poll: 61.0-37.5%
Adjusted National Exit Poll (recorded vote): 52.9-45.6%, 365 EV
True Vote Model: 58.0-40.4%, 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

Posted by on June 25, 2012 in True Vote Models

## 2012 Presidential True Vote and Monte Carlo Simulation Forecast Model

2012 Presidential True Vote and Monte Carlo Simulation Forecast Model

Richard Charnin
June 22,2012

The model will be run on a periodic basis up to Election Day.
a) The True Vote Model is based on estimated turnout and vote share assumptions
b) The Simulation model is based on the latest state and national polls.

NOV.5 UPDATE: VIEW FINAL FORECAST HERE

It is important to note that the True Vote is never the same as the recorded vote. In 2008, Obama had 58% in the unadjusted state exit poll aggregate and 58% in the 1988-2008 True Vote Model. But his recorded vote share was just 52.9%. Therefore, assuming the same 5% red-shift differential, Obama needs at least a 55% True Vote share to win the popular vote.

Rasmussen is a GOP pollster who provides a Likely Voter (LV) subset of the total number of Registered Voters (RV). The majority of registered voters excluded by the Likely Voter Cutoff Model are Democrats.

Election Model Projections: 2004-2010

The 2004 Election Model weekly projections started in July and were based on 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. It projected Kerry winning 337 electoral votes with 51.8% of the two-party vote, closely matching the unadjusted National Exit Poll (51.7%). The election was stolen.

The 2006 House Trend Forecast Model was based on 120 Generic polls. It projected that the Democrats would capture 56.43% of the vote and was virtually identical to the unadjusted National Exit Poll (56.37%). The NEP was forced to match the recorded 52-46% vote share. The landslide was denied. Election fraud cost the Democrats 15-20 House seats.

The 2008 Election Model projection was published weekly. The final projection exactly matched Obama’s 365 electoral votes and was within 0.2% of his 52.9% share (a 9.5 million margin). But the model understated his True Vote. The forecast was based on likely voter (LV) polls that had Obama leading by 7%. Registered voter (RV) polls had him up by 13% – before undecided voter allocation. The True Vote Model determined that Obama won by over 22 million votes with 420 EV. His 58% share was within 0.1% of the unadjusted state exit poll aggregate (83,000 respondents). The landslide was denied.

The 2010 Election Forecast Model predicted a 234-201 GOP House based on the final 30 likely voter (LV) Generic polls (the GOP led by 48.7-41.9%). It predicted a 221-214 GOP House based on the final 19 registered voter (RV) polls (the GOP led by 45.1-44.4%). The Final National Exit Poll was a near match to the LV pre-election poll average. The Democratic margin was 6.1% higher in the RV polls than the LVs.

The model predicted a 50-48 Democratic Senate based on 37 LV polls in which the GOP led by 48.1-43.5%. It predicted a 53-45 Democratic margin based on a combination of 18 RV and 19 LV polls in which they led by 45.2-44.6%, a 5.2% increase in margin.

There were no RV polls in the realclearpolitics.com final polling averages. CNN/Time provided RV and LV polling data for 18 Senate races. The Democrats led the RV polls in 11 states (49.2-40.6%) and the LV subset in 8 (46.6-45.8%), an 8% difference in margin.

Take the Election Fraud Quiz.

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

## Massive 1988-2008 Exit Poll Discrepancies: A Probability Analysis

Massive 1988-2008 Exit Poll Discrepancies: A Probability Analysis

Richard Charnin
June 21, 2012

This post reviews probability calculation methods used to analyze the 1988-2008 unadjusted state and national exit polls.

The 1988-2008 Unadjusted State and National Exit Poll Spreadsheet Database consists of individual election worksheets. The tables contain unadjusted state exit poll samples, vote share, margin, votes cast and recorded, margin of error, win probability, electoral vote, region and the weighted aggregate of the unadjusted state exit poll shares. In addition, the workbook includes graphics, exit poll time lines, red-shift analysis, early vs. late voting statistics, net uncounted votes, 2006 and 2010 exit polls, etc.

The Democrats won the 1988-2008 unadjusted state exit polls by 52-42% and the recorded vote by just 48-46%, an 8% reduction in margin. In 274 state exit polls, there were approximately 375,000 respondents – a very large sample of six presidential elections. Like much other statistical analysis, the results are based on the Law of Large Numbers.
http://en.wikipedia.org/wiki/Law_of_large_numbers

Unadjusted exit polls tell us exactly how respondents said they voted.
Exit polls are always adjusted to conform to the recorded vote count.
The discrepancy is the difference between the exit poll and recorded vote margins.

The True Vote Model estimates voter intent based on mortality, turnout and vote shares. It has confirmed the unadjusted exit polls to within 1%.

The polling margin of error (MoE) is a function of the number of respondents (n) and 2-party shares.
MoE = 1.3 * sqrt (p * (1-p)/n), where 1.3 is 30% cluster effect factor.

Example: Florida 2004 (2862 respondents)
Kerry led the exit poll by 50.8-48.0% (two-party 51.4-48.6)%.
But Bush won the recorded vote by 52.1-47.1%

The FL exit poll MoE = 2.38% = 1.3 * 1.96 * sqrt (.514*.486/2862)
Kerry’s 2-party vote (x) would be expected to fall within the following interval 95% of the time.
Mean – MoE < x < Mean+ MoE or
49% < x < 53.8%.

The probability that Kerry won FL is given by the Normal Distribution Function:
http://en.wikipedia.org/wiki/Normal_distribution

P = Normdist (Poll, .5, MoE/1.96, true)
P = 87.6% = Normdist (.514, .5, .0238/1.96, true)

Example: 2004 National Exit Poll

Kerry led the unadjusted poll (13660 respondents) by 51.7-47.0% (2-party: 52.3-47.7%). But Bush won the recorded vote by 50.7-48.3%.
The National exit poll margin of error was 1.1%.

Sample Kerry Bush Other
13,660 7,064 6,414 182
Share 51.7% 47.0% 1.3%

The probability P that Kerry won the popular vote is calculated as:
P = 99.97% = Normdist (.523, .5, .011/1.96, true)
Let’s be conservative and increase the margin of error to 2.0%.
P = 98.7% = Normdist (.523, .5, .02/1.96, true)

The National Exit Poll, with no change to the 13660 respondents) was forced to match the recorded vote. This is standard procedure for all exit polls. The NEP implied that 43% of the 2004 electorate (52.6 million) were returning Bush 2000 voters. But Bush only had 50.5 million recorded votes in 2000. Approximately 2.5 million died and another 1-2 million did not return in 2004. There could have no more than 46-47 million returning Bush voters. The 2004 NEP indicated an impossible 110% Bush 2000 voter turnout in 2004. The exit pollsters forced an impossible poll to match an impossible vote using impossible returning voter weights.

Example: 274 state presidential exit polls (1988-2008)
A total of 226 polls (82.4%) shifted from the poll to the vote in favor of the Republican. Only 48 shifted to the Democrat. Normally, as in coin-flipping, there should have been a shift of 150 to the Republican and 150 to the Democrat. What is the probability P of 226 polls red-shifting to the Republicans?

The Binomial distribution function:
http://en.wikipedia.org/wiki/Binomial_distribution

Unfortunately, the spreadsheet Binomial function cannot calculate the probability; the inputs are too large. We need to break the problem into four equal pieces: 56 of 68 exit polls red-shift with probability p.

p = Binomdist (56, 68, .5, false)
P = p*p*p*p (equivalent to P = Binomdist (224, 272, .5, false))
P = 3.7E-31
P = 1 in 2.7 million trillion trillion trillion

Note E-31 is scientific notation for 31 places to the right of the decimal point. For instance, E-3 represents .001 or 1/1000

Example: The MoE was exceeded in 126 of 274 state exit polls
Only 14 would normally be expected to since there is a 5% probability that the exit poll margin of error would be exceeded in an election. Of the 126 polls, 123 moved in favor of the Republicans (only 7 would be expected). Three favored the Democrat.

The Poisson function is used for analyzing a series of events (like in queuing systems) in which each event has a very low probability of occurrence.
http://en.wikipedia.org/wiki/Poisson_distribution

The probability P that 123 out of 274 would favor the Republican is:
P = 5E-106 = Poisson (123, .025*274, false)
The probability is ZERO. There are 106 places to the right of the decimal.
P = .0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 000005
P = 1 in 1.8 billion trillion trillion trillion trillion trillion trillion trillion trillion.

For each presidential election, the following table summarizes a) the number of state elections which there was a Republican red-shift from the exit poll to the vote, b) the number (n) of states in which the margin of error was exceeded in favor of the Republican, c) the probability that n states would red-shift beyond the MoE to the Republican, d) the Democratic unadjusted aggregate state exit poll share, e) the Democratic recorded share, f) the differential between the exit poll and recorded vote.

The Ultimate Smoking Gun that proves Systemic Election Fraud:

Year RS >MoE Probability.. Exit Vote Diff
1988 20.. 11… 5.0E-11….. 50.3 45.7 4.6 Dukakis may very well have won a close election.
1992 44.. 26… 2.4E-25….. 47.6 43.0 4.6 Clinton won in a landslide, much bigger than recorded.
1996 43.. 16… 4.9E-13….. 52.6 49.3 3.3 Clinton won in a landslide, much bigger than recorded.
2000 34.. 12… 8.7E-09….. 50.8 48.4 2.4 Gore won by 5-7 million True votes.
2004 40.. 22… 3.5E-20….. 51.1 48.3 2.8 Kerry won a 10 million True vote landslide.
2008 45.. 36… 2.4E-37….. 58.0 52.9 5.1 Obama won a 23 million True vote kandslide.

Total 226-123 ; 5.0E-106… 51.8 47.9 3.9

Read this excellent article by Bob Fitrakis in The Free Press.

Polling is not an exact science. But the 300 exit poll samples over six presidential elections confirm beyond any doubt that the massive discrepancies must be due to election fraud.

The exit pollsters are funded by the National Election Pool. The pollsters always seem to get it “wrong” in the US, and then have to make impossible adjustments to get it “right”. Why do the exit pollsters always get it “wrong” in the US but get it “right” in the Ukraine and Republic of Georgia?

Any standard statistical/probability analysis applied to publicly available data results in only one reasonable conclusion: election fraud is pervasive and systemic.

Take the Election Fraud Quiz.

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

Posted by on June 21, 2012 in True Vote Models, Uncategorized

## 9/19/ 2012 Presidential True Vote and Election Fraud Simulation Model: Obama 320 EV; 100% Win Probability

9/19/ 2012 Presidential True Vote/Election Fraud Simulation Model:Obama 320 EV; 100% Win Probability

Richard Charnin
Sept.19, 2012

The analysis assumes the election is held on the latest poll date:
2012 Presidential True Vote and Monte Carlo Simulation Forecast Model

Forecast Summary
Obama has jumped out to a commanding 49-44% lead in the battleground state polls. He has 320 expected electoral votes based on his state win probabilities. The 500 trial Monte Carlo simulation indicates that if the election were held today, he would have a 100% win probability (he won all 500 election simulation trials). But it’s still too early to project him a winner.

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

Obama needs at least a 55% True Vote to overcome the Fraud factor. He has held a steady 4% lead in the state polls since April. The polls are anticipating the inevitable 5% reduction in Obama’s True Vote. Immediately after the Democratic Convention, Obama moved into a 5% lead in the Gallup (RV) and Rasmussen (LV) national tracking polls, but the polls are tied once again.

The forecast model is a combination of a) a pre-election Monte Carlo Simulation Model, which is based on the latest state polls, and b) the True Vote Model, based on a feasible estimate of new and returning 2008 voters and corresponding estimated vote shares. The model will be updated periodically for the latest state and national polls.

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.

``` 9/19/2012 Model.......... Obama Romney True Vote...... 55.25% 44.75% Expected EV.... 379.64 158.36 Snapshot EV.... 380 158 EV Win Prob.... 99.97% 0.03%```

``` State Polls Average........ 49.3% 44.4% Projection..... 52.5% 47.5% Pop. Win Prob.. 94.8% 5.2% Expected EV.... 320.2 217.8 Snapshot EV.... 322 216 National Polls Average....... 48.20% 45.30% Projection.... 51.45% 48.55% Pop. Win Prob.. 92.2% 7.8% Gallup......... 47.0% 46.0% Rasmussen...... 46.0% 47.0% ```

```Simulation Projection..... 52.5% 47.5% Mean EV........ 320.4 217.6 Max EV......... 351 187 Min EV......... 278 260 EV Win Prob.... 100.0% 0.0% ```

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 (76,000 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%. As usual, the unadjusted state and national exit polls were 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 options for the simulation model. Both should be used and the results compared. The default option uses the TVM projected state vote shares. The second option uses projections based on the latest pre-election state polls.

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 ‘Polls” worksheet which will be used for trend analysis. The data is displayed graphically in the ‘PollChart’ worksheet. A histogram of the Monte Carlo Simulation (500 trials) is displayed in the ‘ObamaEVChart’ worksheet.

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 go one way.
2. The Theoretical EV is the product sum of the state electoral votes and win probabilities. A simulation or meta-analysis is not required to calculate the expected EV.
3. The Mean EV is the average electoral vote in the 500 simulated elections.

The Mean EV will be close to the Theoretical EV, illustrating the Law of Large Numbers. The snapshot EV will likely differ slightly from the Theoretical EV, depending on the number of state election projections that fall within the margin of error.

Obama’s electoral vote win probability is the percentage of 500 simulated election trials that he won.

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% recorded. 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 the vote shares by entering an incremental adjustment in the designated input cell. A red flag would be raised if the match required that Obama capture 85% of returning Obama voters while Romney gets 95% of returning McCain voters (a 10% net defection).

- Adjusting 2008 voter turnout in 2012 in order to force a match to the aggregate projected poll shares. For example, if McCain voter turnout is required to be 10-15% higher than Obama’s, that would also raise a red flag.

- Setting the returning voter option to assume the 2008 recorded vote. This is an implicit assumption that the 2008 recorded vote was the True Vote. Of course, the 2008 election was highly fraudulent, but this is what the election forecasters effectively do: they ignore the fraud factor. The resulting model vote shares would then closely match the LV polls and would suggest that Romney has a good chance of winning a rigged election.

In any case, check the simulated, theoretical and snapshot electoral vote projections and the 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 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.

In 2006, the adjusted National Exit Poll indicated that the Democrats won the House by a 52-46% vote share. My 120 Generic Poll Forecasting Regression Model indicated that the Democrats would capture 56.43% of the vote. It was within 0.06% of 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).

The exit pollsters have never explained the massive 11% state exit poll margin discrepancy, much less the impossible National Exit Poll 17% discrepancy. If they do, they will surely claim that the discrepancies were due to flawed polling samples. Nor can they explain the rationale of using impossible returning voter weight adjustments to force the exit polls to match the recorded votes in the 1988, 1992, 2004 and 2008 presidential 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, the 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 are allocated. They have also been confirmed by the True Vote Model. The loop is closed when implausible/impossible exit polls are forced to match bogus recorded votes that were predicted by biased LV pre-election polls.

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

Posted by on April 26, 2012 in 2012 Election, True Vote Models

## The 2004-2008 County Presidential True Vote Database Model

The 2004-2008 County Presidential True Vote Database Model

March 23, 2012

The 2004-2008 County True Vote Database Model has been restructured. Just enter the state code in cell A2 of the new “Input” sheet.

The objective of the model is to determine the most fraudulent counties in 2008. No model is perfect, but the TVM provides a good estimate of election fraud as measured by vote share and vote count discrepancies in margin from the recorded vote.

The following states are currently in the database. More states will be added:
AZ CA CO FL GA IA IL IN MA MI MO NC NM NV NY OH OR PA TN TX WI

In 2004, Kerry lost the national recorded vote by 50.7-48.3%. He had 51.1% in the unadjusted state exit polls (76,000 respondents) and 51.7% in the unadjusted National Exit Poll (a subset with 13,660 respondents). The True Vote Model sensitivity analysis provides convincing evidence that Kerry won the election easily.

In 2008, Obama won the national recorded vote by a 52.9-45.6% margin. He had a 58% share in the unadjusted state exit polls (83,000 respondents) and a whopping 61% in the unadjusted National Exit Poll (a subset with 17,836 respondents).

The key stats are shown in the “Input” sheet. These include the state True Vote table and discrepancies between Obama’s True county vote margin and the recorded margin. Calculation details are displayed in the “Model” sheet.

The 2008 Election Model projection exactly matched Obama’s 365 electoral votes and was within 0.2% of his 52.9% share (a 9.5 million margin).

But the model understated his True Vote. The forecast was based on final likely voter (LV) polls that had Obama leading by 7%. The registered voter (RV) polls had him up by 13% – before undecided voter allocation. The landslide was denied.

The Final 2008 National Exit Poll was forced to match the recorded vote by indicating an impossible 103% turnout of living Bush 2004 voters and 12 million more returning Bush than Kerry voters. Given Kerry’s 5% unadjusted 2004 exit poll and 8% True Vote margin, one would expect 7 million more returning Kerry than Bush voters – a 19 million discrepancy from the Final 2008 NEP. Another anomaly: The Final 2008 NEP indicated there were 5 million returning third party voters – but only 1.2 million were recorded in 2004. Either the 2008 NEP or the 2004 recorded third-party vote share (or both) was wrong.

The True Vote Model determined that Obama won by over 22 million votes with 420 EV. His 58% share was within 0.1% of the unadjusted state exit poll aggregate (83,000 respondents).

True Vote margins are calculated based on the returning voter method: The default method is that 2004 voters return to vote in 2008 in proportion to the 2004 state exit poll shares. Optionally, set code 1 in cell A5 to calculate returning voters in proportion to the 2004 recorded vote shares.

If the recorded vote option is used, county vote discrepancies will be lower than they would be if the default method was used. But since the 2004 recorded votes were fraudulent, unadjuted 2004 exit polls (the default) should be used to calculate returning voters to provide a better estimate of the true discrepancy.

The model automatically adjusts state and county vote shares based on the differential between the unadjusted state and national exit polls.

The user has the option of overriding the returning voter mix as well as the vote shares. Enter incremental percentage changes to a) Kerry’s returning vote counts (an automatic offsetting change is made to Bush’s vote count) and b) to Obama’s shares of new and returning voters (an automatic offsetting change is made to McCain’s vote shares.

Default 2004 living voter turnout in 2008 is set to 97%.

The model indicates that the following counties were the most fraudulent:
Wisconsin
Obama recorded share: 56.2%, Exit Poll: 63.3%, True Vote Model: 58.8%
Waukesha,Sheboygan,Washington,Milwaukee

Ohio
Obama recorded share: 51.4%, Exit Poll: 56.3%, True Vote Model: 56.2%
Cuyahoga,Franklin,Hamilton,Montgomery,Summit

Florida
Obama recorded share: 50.9%, Exit Poll: 52.1%, True Vote Model: 54.7%
Palm Beach, Miami-Dade, Broward, Brevard, Hillsborough

New York
Obama recorded share: 62.8%, Exit Poll: 71.5%, True Vote Model: 68.3%
Nassau, Suffolk, Erie, Queens, Westchester

Pennsylvania
Obama recorded share: 54.5%, Exit Poll: 63.8%, True Vote Model: 62.0%
Philadelphia, Allegheny, Bucks, Westmoreland, Montgomery, Delaware

The correlation ratio is a statistical measure of the relationship between Obama’s recorded vote share and the True Vote discrepancy. In general, there is a strong negative correlation between the two variables. This indicates that as Obama’s recorded county vote share increases (decreases) the discrepancy decreases (increases). This is an indication that GOP counties are the most fraudulent (measured by vote share margin discrepancy).

The correlation ratio is in the range from -1 to +1 (-1 is a perfectly negative correlation and +1 is perfectly positive). A near zero correlation indicates little or no relationship. A positive value indicates that the variables generally move in the same direction: as one variable increases (decreases), the other also increases (decreases). A negative value indicates the opposite: as one variable increases (decreases) the other decreases (increases). The correlation is a strong one if it is higher than 0.50 (positive) or lower than -0.50 (negative).

For example, in Ohio 2004 the -0.82 correlation indicated that Bush counties were more fraudulent than Kerry counties (based on vote share margin discrepancies). In 2008, the -0.50 correlation was not as strong but still significant.

North Carolina was an unusual exception. In 2004 there was a near-zero (-.01) correlation, indicating no relationship between county partisanship and election fraud. But in 2008, the strong negative (-0.72) correlation indicates that election fraud was more prevalent in GOP than Democratic counties.

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

## 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:

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%. Uncounted votes (Total Votes Cast) are not included in the True Vote calculations.

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…
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…
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…
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…
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…
Margin: Northampton York Westmoreland

## 1988-2008 Unadjusted Presidential Exit Polls: A 51.9-41.7% Average Democratic Margin

1988-2008 Unadjusted Presidential Exit Polls: A 51.9-41.7% Average Democratic Margin

Richard Charnin
Nov. 13, 2011
Updated: May 9, 2012

The 1988-2008 Unadjusted State and National Exit Poll Spreadsheet Database contains a wide selection of tables and graphs for presidential election analysis.

The data source is the Roper website.

Unadjusted exit poll data reflect actual samples. Vote shares have closely matched the corresponding True Vote Model, which calculates feasible estimates of returning and new voters. But exit poll demographics displayed in the mainstream media are always forced to match the recorded vote by “adjusting” the category crosstab weightings and/or vote shares. Adjusted “final” exit polls do not reflect actual voter response, but merely parrot the recorded (fraudulent) vote. The fraud factor is assumed to be zero in the final published polls.

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

To force State and National Exit Polls to match the recorded vote, ALL demographic category weights and/or vote shares must be adjusted.

In 2000, Gore won the aggregate of the unadjusted state exit polls (58,000 respondents) by 50.8-44.4%, a 6 million vote margin. But he won the recorded vote by just 540,000 votes (48.4-47.9%). There were six million uncounted votes, the vast majority (75-80%) for Gore. Uncounted ballots accounted for 3-4 million of the 5.5 million vote discrepancy. Vote switching and ballot stuffing may account for the remaining 1-2 million.

In 2004, Bush won the recorded vote by 50.7-48.3%. The unadjusted National Exit Poll (13,660 respondents) indicated that Kerry won by 51.7-47.0%. Exit pollsters Edison/Mitofsky suggested the reluctant Bush responder (rBr) hypothesis to explain the difference: there must have been 56 Kerry responders for every 50 Bush responders. There was no evidence to back it up.

Mitofsky used the same argument to explain the large 1992 exit poll discrepancies. Clinton had 43.0% recorded, a six million vote margin; he had 47.6% in the unadjusted exit poll and had a 16 million landslide. Mitofsky never mentioned the 1992 Vote Census which showed that there were 10 million more votes cast than recorded. Uncounted ballots accounted for half the 10 million discrepancy in margin.

Forcing the exit poll to match the recorded vote

The pollsters applied their unsupported hypothesis by forcing the National Exit Poll to match the recorded vote. They indicated that 43% of 122.3 (52.6 million) of the 2004 electorate were returning Bush 2000 voters and 37% returning Gore voters. But 52.6 million was an impossible statistic; it implied a 110% turnout of living Bush 2000 voters.

Bush only had 50.5 million votes in 2000. Approximately 2.5 million died prior to the 2004 election and one million did not return to vote. Therefore, no more than 47 million Bush 2000 voters (38.4% of the 122.3 million) could have returned. There had to be 5.6 million PHANTOM BUSH VOTERS.

In fact, Kerry led the unadjusted state exit poll aggregate (76,000 respondents) by 51.1-47.6%. He led the unadjusted National Exit Poll (13,660 respondents) by 51.7-47.0%.

Therefore, since the National Exit Poll was forced to match the recorded vote with an impossible number of returning Bush voters, the recorded vote must have been impossible. Simple mathematics proves election fraud.

The True Vote Model (TVM) indicated that Kerry had 53.6%. Why the difference between the TVM and the unadjusted state and national exit polls? The exit pollsters apparently designed their 2004 sample based on the bogus 2000 recorded vote which indicated that Gore won by just 540,000 votes (48.4-47.9%). On the other hand, the TVM uses a feasible estimate of returning voters from the prior election. Gore won the unadjusted state exit polls by 50.8-44.5%; he won the unadjusted National Exit Poll by 48.5-46.3%.

In 2008 Obama led the unadjusted state exit poll aggregate (83,000 respondents) by 58.0-40.5%. He led the unadjusted National Exit Poll (17,836 respondents) by 61.0-37.2%. As usual, the NEP was forced to match the recorded vote (Obama by 52.9-45.6%).

Why the discrepancy? The National Exit Poll was forced to match the bogus recorded vote by indicating that returning Bush and Kerry voters comprised 46% and 37%, respectively, of the electorate. The pollsters implied that there were 12 million more returning Bush than Kerry voters. But Kerry won the unadjusted National Exit Poll by 6 million votes and the True Vote Model by 10 million.

The following examples illustrate how the exit pollsters rigged the Final 2004 National Exit Poll demographic crosstabs to force them to match the recorded vote.

Bush Approval
The pollsters had to inflate Bush’s pre-election approval rating by a full 5% in order to force a match to the recorded vote – and perpetuate the fraud. Bush had 50.3% approval in the unadjusted state exit poll aggregate, but just 48% approval in 11 final pre-election polls. Therefore, the unadjusted exit polls may have understated Kerry’s True Vote by 2%. In order to force the Final National Exit Poll to match the recorded vote, the exit pollsters had to increase Bush approval to 53%, a full 5% over the 48% average of 11 pre-election polls. If Bush’s true approval was 48%, that means Kerry had 53.6% – matching the True Vote Model.

Party-ID
In order to force a match the recorded vote, the pollsters had to “adjust” the state exit poll Dem/Rep Party-ID split from 38.8/35.1% to 37/37% in the Final National Exit Poll.

There was a near-perfect 0.99 correlation between Bush’s unadjusted state exit poll shares and approval ratings and a 0.93 correlation between his shares and Republican Party-ID.

This chart displays Bush’s unadjusted state exit polls, approval ratings and Republican Party-ID.

The True Vote Model (TVM) is based on Census votes cast, mortality, prior election voter turnout and National Exit Poll vote shares. The TVM closely matched the exit polls in each election. In 2008, it was within 0.1% of Obama’s 58.0% unadjusted exit poll share.

The Democrats led the 1988-2008 vote shares measured by…
1) Recorded Vote: 48.08-45.96%
2) Unadjusted State Exit Poll Aggregate:51.88-41.71% (370,000 respondents)
3) Unadjusted National Exit Poll: 51.86-41.65 (85,000 respondents)
4) True Vote Model (methods 2-3): 51.6-42.9%
5) True Vote Model (method 4): 53.2-41.0%
6) State Exit Polls (WPE/IMS) method: 51.0-43.0%

The Democrats won the exit poll and lost the recorded vote in the following states:
1988: CA IL MD MI NM PA VT (Dukakis won the unadjusted Nat Exit Poll 50-49%)
1992: AK AL AZ FL IN MS NC OK TX VA
1996: AK AL CO GA ID IN MS MT NC ND SC SD VA
2000: AL AR AZ CO FL GA MO NC TN TX VA (Gore needed just ONE state to win)
2004: CO FL IA MO NM NV OH VA (Kerry would have won if he carried FL or OH)
2008: AL AK AZ GA MO MT NE

This barchart displays the trend in unadjusted exit poll, True Vote and recorded vote shares from 1988-2008.

1988-2008 Election Fraud
The discrepancies between the official recorded vote and unadjusted exit polls are in one direction only. This cannot be coincidental. The True Vote Model is confirmed by the unadjusted exit polls – and vice versa.

In the 1988-2008 presidential elections, there was a massive 8% discrepancy between the exit polls (52D-42R) and the recorded vote (48D-46R). The Probability P of the discrepancy is less than:
P = 8E-10 = 1- Normdist (.52, .48, .012/1.96, true)
P = 1 in 1.2 billion

Example: 274 state presidential exit polls (1988-2008)
A total of 226 polls (82.4%) shifted from the poll to the vote in favor of the Republican. Only 48 shifted to the Democrat. Normally, as in coin-flipping, there should have been a shift of 150 to the Republican and 150 to the Democrat. What is the probability P of 226 polls red-shifting to the Republicans?

The Binomial distribution function:
http://en.wikipedia.org/wiki/Binomial_distribution

Unfortunately, the spreadsheet Binomial function cannot calculate the probability; the inputs are too large. We need to break the problem into four equal pieces: 56 of 68 exit polls red-shift with probability p.

p = Binomdist (56, 68, .5, false)
P = p*p*p*p (equivalent to P = Binomdist (224, 272, .5, false))
P = 3.7E-31
P = 1 in 2.7 million trillion trillion trillion

Note E-31 is scientific notation for 31 places to the right of the decimal point. For instance, E-3 represents .001 or 1/1000

Example: The MoE was exceeded in 126 of 274 state exit polls
Only 14 would normally be expected to since there is a 5% probability that the exit poll margin of error would be exceeded in an election. Of the 126 polls, 123 moved in favor of the Republicans (only 7 would be expected). Three favored the Democrat.

The Ultimate Smoking Gun that proves Systemic Election Fraud:

The Poisson function is used for analyzing a series of events (like in queuing systems) in which each event has a very low probability of occurrence.
http://en.wikipedia.org/wiki/Poisson_distribution

The probability P that 123 out of 274 would favor the Republican is:
P = 5E-106 = Poisson (123, .025*274, false)
The probability is ZERO. There are 106 places to the right of the decimal.
P = .0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 000005
P = 1 in 1.8 billion trillion trillion trillion trillion trillion trillion trillion trillion.

For each presidential election, the following table summarizes a) the number of state elections which there was a Republican red-shift from the exit poll to the vote, b) the number (n) of states in which the margin of error was exceeded in favor of the Republican, c) the probability that n states would red-shift beyond the MoE to the Republican, d) the Democratic unadjusted aggregate state exit poll share, e) the Democratic recorded share, f) the differential between the exit poll and recorded vote.

Year RS >MoE Probability.. Exit Vote Diff
1988 20.. 11… 5.0E-11….. 50.3 45.7 4.6 Dukakis may very well have won a close election.
1992 44.. 26… 2.4E-25….. 47.6 43.0 4.6 Clinton won in a landslide, much bigger than recorded.
1996 43.. 16… 4.9E-13….. 52.6 49.3 3.3 Clinton won in a landslide, much bigger than recorded.
2000 34.. 12… 8.7E-09….. 50.8 48.4 2.4 Gore won by 5-7 million True votes.
2004 40.. 22… 3.5E-20….. 51.1 48.3 2.8 Kerry won a 10 million True vote landslide.
2008 45.. 36… 2.4E-37….. 58.0 52.9 5.1 Obama won a 23 million True vote kandslide.

Total 226-123 ; 5.0E-106… 51.8 47.9 3.9