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.

 

Track Record: 2004-2012 Election Forecast and True Vote Models

Track Record: 2004-2012 Election Forecast and True Vote Models

Richard Charnin
Jan. 19, 2013

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

Note that the Election Model forecasts are based on final state pre-election Likely Voter (LV) polls, a subset of the total Registered Voters (RV) polled. The LVs always understate Democratic voter turnout; many new (mostly Democratic) voters are rejected by the Likely Voter Cutoff Model (LVCM). In addition, pre-election polls utilize previous election recorded votes in sampling design, rather than total votes cast. Total votes cast include net uncounted votes which are 70-80% Democratic. The combination of the LVCM and uncounted votes results in pre-election polls understating Democratic turnout – and their projected vote share.

2004 Election Model
Kerry Projected 51.8% (2-party), 337 EV (simulation mean), 322 EV snapshot
Adjusted National Exit Poll (recorded vote): 48.3-50.7%, 252 EV
Unadjusted State exit poll aggregate: 51.1-47.6%, 349 EV snapshot, 336 EV expected Theoretical)
Unadjusted National Exit Poll: 51.7-47.0%
True Vote Model: 53.6-45.1%, 364 EV

2004 Election Model Graphs
State aggregate poll trend
Electoral vote and win probability
Electoral and popular vote
Undecided voter allocation impact on electoral vote and win probability
National poll trend
Monte Carlo Simulation
Monte Carlo Electoral Vote Histogram

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

2008 Election Model
Obama Projected: 53.1-44.9%, 365.3 expected EV; 365.8 EV simulation mean; 367 EV snapshot
Adjusted National Exit Poll (recorded vote): 52.9-45.6%, 365 EV
Unadjusted State exit poll aggregate: 58.1-40.3%, 419 EV snapshot, 419 expected EV
Unadjusted National Exit Poll: 61.0-37.5%
True Vote Model: 58.0-40.4%, 420 EV

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

2010 Midterms Overview
True Vote Model Analysis

2012 Election Model
Obama Projected: 51.6% (2-party), 332 EV snapshot; 320.7 EV expected; 321.6 EV simulation 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

2012 Model Overview
Electoral Vote Trend
Monte Carlo Simulation Electoral Vote Frequency Distribution

 

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
4. Obama had 59% of new voters; McCain had 41%
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. 

National Exit Poll Crosstab Adjustments
The 2012 National Exit Poll Party-ID category indicates a 39D-32R-29I split. Was the unadjusted Democratic share lowered to force a match to the recorded vote? Let’s consider the 2004 and 2008 elections.

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

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

In 2004, Bush had a 48% average approval rating in 11 pre-election polls and 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%
Unadjusted National Exit Poll: 56.37%

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

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

 

The Late Recorded Votes: A confirmation of the True Vote?

The Late Recorded Votes: A confirmation of the True Vote?

Richard Charnin
Updated: Jan.7, 2013

The late vote timeline included in the 2012 True Vote Model shows that Obama’s lead increased dramatically after Election Day. He won the 11.7 million late votes recorded after Election Day by 58.0-38.3%, but led the first 117.4 million recorded by just 50.3-48.1%. Once again, as in every election since 2000, the Democratic late vote share exceeded the Election Day share by a substantial margin. What is the cause of this anomaly? Some possible reasons are given below.

Dave Leip’s US Election Atlas and Wikipedia provided daily state vote updates.

Obama vote share margins:
Election Day: 50.3-48.1% (2.2% of 117.45 million votes).
Late vote 58.0-38.3 (19.7% of 11.68 million votes).
Total vote: 51.03-47.19% (3.8% of 129.13 million votes.
Weighted late vote: 54.0%-41.8% (12.2%).
(Late state vote shares are weighted by total votes cast)

Obama 2-party shares and margins:
51.2-48.8% Election Day Recorded share (2.4%)
56.3-43.7% Late Vote share weighted by total recorded vote (12.6%)
52.0-48.0% Total vote (4.O%)
60.2-39.8% Unweighted Late Vote share (20.4%)
56.1-43.9% True Vote Model (12.2%)

2012 Late Vote Timeline
On……Obama led by…
Nov. 8 50.34-48.07% of 117.45 million recorded votes
Nov. 9 50.43-47.97% of 119.58 (2.13 late)
Nov.10 50.51-47.87% of 122.20 (4.75 late)
Nov.11 50.52-47.86% of 122.58 (5.13 late)
Nov.13 50.55-47.82% of 122.94 (5.49 late)
Nov.14 50.61-47.76% of 123.73 (6.27 late)
Nov.16 50.66-47.69% of 124.69 (7.24 late)
Nov.20 50.73-47.61% of 125.53 (8.07 late)
Nov.25 50.80-47.50% of 126.87 (9.41 late)
Nov.28 50.88-47.38% of 127.74 (10.29 late)
Nov.29 50.90-47.36% of 127.87 (10.42 late)
Dec.05 50.94-47.31% of 128.36 (10.90 late)
Dec.21 50.96-47.28% of 128.74 (11.28 late)
Final
Dec.31 51.03-47.19% of 129.13 (11.68 late)

Election Day and Late vote shares
(Late votes in thousands)
* indicates suspicious anomaly
…………….EDay Late Late Votes (000)
Total………..50.3% 58.0% 11,677

Alabama………39% 37% 312 *
Alaska……….41% 40% 80
Arizona………43% 47% 666 *
Arkansas……..37% 36% 25
California……59% 63% 3,609 *
Colorado……..51% 54% 222 *
Connecticut…..51% 59% 1,307 *
Delaware……..59% 80% 0
D. C…………91% 90% 50
Florida………50% 53% 182 *
Georgia………45% 49% 47 *
Hawaii……….71% 72% 0
Idaho………..32% 33% 45
Illinois……..57% 65% 130 *
Indiana………44% 49% 88 *
Iowa…………52% 63% 24 *
Kansas……….38% 37% 39
Kentucky……..38% 29% 117 *
Louisiana…….58% 41% 1
Maine………..56% 57% 64
Maryland……..62% 65% 236 *
Massachusetts…61% 55% 132 *
Michigan……..53% 71% 222 *
Minnesota…….53% 79% 6
Mississippi…..44% 46% 85
Missouri……..44% 71% 12
Montana………42% 40% 49
Nebraska……..38% 44% 27
Nevada……….52% 69% 3
New Hampshire…52% 35% 10
New Jersey……58% 61% 327 *
New Mexico……53% 60% 13
New York……..63% 68% 902 *
North Carolina..48% 48% -4 *
North Dakota….39% 15% 3
Ohio…………50% 59% 229 *
Oklahoma……..33% 32% 2
Oregon……….53% 58% 330
Pennsylvania….52% 43% 292 *
Rhode Island….63% 60% 29
South Carolina..44% 47% 111 *
South Dakota….40% 44% 0
Tennessee…….39% 40% 8
Texas………..41% 43% 53
Utah…………25% 23% 106
Vermont………67% 65% 61
Virginia……..51% 65% 160 *
Washington……55% 57% 1,217
West Virginia…36% 36% 29
Wisconsin…….53% 48% 15 *
Wyoming………28% 25% 3

No one knows what the unadjusted exit polls look like in 2012. And 19 states were not even exit polled. Maybe we’ll get to see the polls a year from now – when all talk of 2012 election fraud has died down.

The late votes can be viewed as a proxy for the unadjusted state exit polls. In 2008, 10 million late votes matched the polls. Unlike an exit poll survey, however, naysayers cannot use the worn out bogus claims that a) late poll “respondents” are lying about how they voted and b) there is a differential response: Democrats are more anxious to be interviewed than Republicans.

But all we have is the National Exit Poll which is always forced to match the recorded vote and shows that Obama was a 50-48% winner. All demographic crosstabs were forced to conform to the recorded vote. About 80 questions were asked of over 25,000 exit poll respondents, but the most important was missing: Who did you vote for in 2008: Obama, McCain or Other?

The past vote question has always been asked in prior exit polls. It is used as the basis for the True Vote Model to measure prior election voter turnout and vote shares in the current election. The returning voter mix displayed in the adjusted Final National Exit Poll has been determined to be impossible in at least four presidential elections – a clear indicator of a fraudulent vote count.

As in every presidential election since 1988, the Democrat Obama did much better than the recorded vote. If the Late Votes are representative of the total vote, they are another confirmation of systematic election fraud. Why would the late votes always show a sharp increase in the Democratic vote share?

In the 2000, 2004, and 2008 elections, late votes recorded after Election Day showed a dramatic increase in Democratic vote shares. The late votes closely matched the state and national exit polls and the True Vote Model. The anomaly is also apparently occurring in 2012.

2000: 102.6 million votes recorded on Election Day. Gore led 48.3-48.1%.
Gore had 55.6% of the 2.7 million late votes.

2004: 116.7 million votes recorded on Election Day. Bush led 51.6-48.3%.
Kerry had 54.2% of the 4.8 million late 2-party votes.

2008: 121 million votes recorded on Election Day. Obama led 52.3-46.3%.
Obama won 10.2 million late votes by 59.2-37.5%. He won the 131 million recorded votes by 52.9-45.6%, a 9.5 million vote margin. But he did much better in the unadjusted National Exit Poll: 61-37% (17,836 respondents, a 31 million vote margin. He also won the unadjusted state exit poll aggregate (82,388 respondents) by 58.0-40.5%, a 23 million margin. Obama had an identical 58.0% in the True Vote Model, exactly matching and confirming the state exit polls.

But this is the kicker: the exit polls and True Vote Model vote shares closely matched the 10 million late recorded votes!

To summarize Obama in 2008:
1- National Exit poll (17,836 respondents): 61.0%
2- State exit poll weighted aggregate (82,388 respondents): 58.0%
3- True Vote Model: 58.0%
4- Late vote (10.2 million): 59.2%
5- Recorded vote: 52.9%

The CNN 2008 Election site shows Obama winning by 66.88-58.43 million votes, an 8.45 million margin. The final recorded vote was 69.50-59.95, a 9.55 million margin. Why has CNN not updated the 2008 Election website to include the final 4.15 million votes? Obama won 63% of them.

- Could it be that since the winner has been decided, there is no longer an incentive on the part of the perennial vote thieves to continue switching late votes? Plausible.
- Could it be that the late votes are paper ballots (provisionals, absentees) and not from DREs? Absolutely.
- Could it be that the late votes are coming in from Democratic strongholds? Maybe some, but surely not all.

State vote totals show that the late votes are a reasonable representation of the total electorate. The deviation between the Late and Election Day recorded votes is less than 3% in 20 states. There are 8 in which the deviation exceeds 10% (4 for Obama and 4 for Romney). There are currently 12 with fewer than 3,000 late votes. View the data tables, bar chart and frequency chart in the 2012 Forecasting model.

The consistent Democratic late vote share discrepancies from the Election Day shares are not proof of fraud. But there is no reason why the phenomenon is ignored in the mainstream media and academia. Obviously, without having an accurate composition of the late vote demographics we cannot make a definitive judgment as to whether they are representative of the total electorate. But there are a number of reasons why Obama would be expected to do better in the late vote. The only question is how much better?

1)Late votes are cast on paper ballots, not DREs or optiscans. Therefore we would expect a higher Democratic share than on Election Day because voting machines are rigged. Check.

2)There is no incentive to fix the votes after the election. Check.

3)The increase in Democratic late vote share has occurred in each election since 2000, enforcing the case that it is a structural phenomenon. Check.

4)In 2008, Obama had a 59% share compared to 52% on Election Day. There were 10 million late uncounted votes or 7.8% of 131 million recorded. In 2004, there were 5 million late votes of 122 million (4%). In 2000, 3 million of 105 million (3%). The late vote percentage is rising faster than the increase in minority voters. Check.

5) The average late vote margin exceeded the recorded margin by 11%.
Margins: State Exit Poll aggregate,National Exit Poll,Late Vote share,Recorded share,Deviation
2000 5. 2. 10 0.5 9.5
2004 4. 5. 8. -2.4 10.4
2008 18 24 20 7.3 13.6
2012 na na 14 2.7 11.3


6)Blacks and Hispanics voted at a higher rate for Obama in 2012. Since the total vote declined by 7 million, there were fewer white voters, thus increasing Obama’s total share. Approximately 13% of 2012 voters were black and 10% Latino. Check.

7) Obama’s 2-party late vote shares far exceed his Election Day shares (see above).

Election Model Forecast; Post-election True Vote Model

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

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

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

 

Perspectives on a New Exit Poll Reference

Richard Charnin

Oct. 30, 2012

My comments in bold follow selected paragraphs from Chapter 1 of a new text Exit Polls:Surveying the American Electorate, 1972-2010 by Samuel J. Best, University of Connecticut and Brian S. Krueger, University of Rhode Island.

The authors write:
“Despite the unique insights that exit polls can provide about the composition and preferences of voters, they are seldom used after the days immediately following an election. Once media organizations have tapped the exit polls for explanations of electoral outcomes, they often disappear from the public eye. Some scholars may use them over the next year or two to explore the voting behavior of certain subgroups, such as Hispanics, women, or young people, but for the most part they recede into memory, rarely used beyond the next national election.”

“Unfortunately, few efforts are made to consider the behavior of voters over time. Historical context typically centers on comparing an election to its most recent predecessor, such as contrasting the 2008 presidential election with the 2004 contest. Rarely are exit poll responses tracked and analyzed over time, leaving many important questions understudied. For example, how have various subgroups in the electorate evolved over time? Have their relative sizes in the active electorate increased or decreased? Have their voting patterns grown increasingly partisan or independent? Which subgroups in the electorate behave similarly through the years?”

In 2010, I wrote Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll. My new book was published on Oct. 27, 2012: Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts

I created the 1988-2008 State and National Presidential Exit Poll Spreadsheet Database based on the Roper (University of Connecticut) election data archive.

In the 1988-2008 presidential elections there were 274 state exit polls – and 226 red-shifted to the Republican. The probability is ZERO (3.7E-31). Of the 274 polls, 126 exceeded the margin of error; only 14 would be expected to do so at the 95% confidence level. Once again, the probability is ZERO (8E-75). Of the 126 polls which exceeded the margin of error, 123 red-shifted to the Republican. The probability is ZERO (5.4E-106).

“In the weeks and months that follow, exit polls are used time and again to give meaning to the election results. Newly elected officials rely on them to substantiate policy mandates they claim to have received from voters. Partisan pundits scrutinize them for successful and failed campaign strategies. Even political strategists use them to pinpoint key groups and issues that need to be won over to succeed in future elections.”

But what if the final, adjusted exit polls can be shown to be mathematically impossible? If so, the fact that they must be adjusted to conform to the recorded vote indicates that the recorded vote must also be impossible.

“Unfortunately, these same exit poll results are not easily accessible to members of the public interested in dissecting them. After appearing in the next day’s newspapers or on a politically oriented website, they disappear quickly from sight as the election fades in prominence. Eventually, the exit polls are archived at universities where only subscribers are capable of retrieving the data. But nowhere is a complete set of biennial exit poll results available in an easy-to-use format for curious parties.”

That is why I created the 1988-2008 presidential state and national exit polls using Roper as the source.

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

“Second, and far more troublesome for the reputation of the exit polls, the preliminary exit poll results showed a partisan skew. They overstated Bill Clinton’s share of the vote by 2.5 points in the 1992 presidential race and understated George H. W. Bush’s share by 2.5 points, giving the impression that Clinton won by a far greater margin than the officially tabulated votes indicated.”

“The raw exit poll data had never been deemed “accurate” in the past prior to being weighted to the actual results, but with the release of early results, observable, but correctable, sampling errors gave the impression that the numbers were off.”

One very plausible reason that they were “off” were the 10 million net uncounted votes, the majority from minority precincts that are 90%+ Democratic. The voters were polled, but their votes were not counted. Clinton may have lost millions of other votes due to switched and stuffed ballots. In order to match the 1992 recorded vote, the Final National Exit Poll required that 119% of living Bush 1988 voters turned out in 1992.

“VRS claimed the Democratic overstatement in the raw exit poll data was due to partisan differences in the willingness of voters to complete the exit poll, not to a poor selection of precincts or differential response rates by age, race, or gender. Republicans simply refused to participate at the same rates as Democrats, resulting in there being fewer Republicans in the raw exit poll results than there should have been. Mitofsky speculated that the disparity was due to different intensities of support for the candidates—Democratic voters were just more excited about voting for Clinton than Republican voters were about voting for Bush and, as a result, were more motivated to communicate this message by filling out the exit poll questionnaire; others thought it was due to Republicans in general having less confidence in the mass media.”

Mitofsky may have “speculated” but there is no evidence that Democrats were more responsive to the exit pollsters. In fact, since 2000 response rates in GOP strongholds were higher than comparable Democratic rates. GOP exit poll and vote shares were positively correlated (.25) to state exit poll response. The average Democratic correlation was -0.26. Bush vote shares increased as response rates increased. In 2004, exit poll precinct data showed that response rates were higher in partisan Bush precincts.

“Despite the source of the partisan bias in the raw results, the exit polls were able to characterize accurately the voting patterns of demographic subgroups and partisan constituencies once they were weighted to match the official returns. The problem was that the data could not be corrected until the official results began coming in. As a result, the exit polls were susceptible to inaccurate vote projections on election night, especially early in the evening right after poll closings. Nonetheless, the cautious analysts at VRS still called all the races correctly in the 1992 election.”

The data could not be corrected until the official votes came in? Or was it that the data could not be rigged until the official votes came in? Of course the cautious analysts called the winner correctly – Clinton won easily – but they did not call the vote shares correctly. Clinton won by a much bigger margin than they said he did.

The 2000 Election Debacle
“Network competition to call winners culminated in the disastrous 2000 presidential election, when these systems of race projections broke down, and the networks wound up retracting their calls for the winner in Florida and presumptively the election, not once, but twice on election night. The trouble began early in the evening, when VNS alerted the networks around 7:50 p.m. that their statistical models predicted Al Gore the winner in Florida and that the networks should consider calling the state for Gore. This prediction took place even though only 4 percent of the actual vote had been counted and numerous precincts in the Florida panhandle, which happened to be in the central time zone, remained open until 8 p.m.”

If the exit polls show a clear winner – as they did in Florida – the fact that just 4% of the votes were recorded is irrelevant. The exit polls were completed by 7:50pm – and panhandle precincts were exit polled throughout the day. Calling the race 10 minutes before the polls closed was of no consequence. Gore won the Florida exit poll (1816 respondents) by a whopping 53.4-43.6%, far beyond the 3% margin of error.

“Less than ten minutes later, the decision desks at all the networks and the AP agreed with VNS and announced Gore the winner in Florida. Over the next hour-and-a-half, VNS discovered that vote-count data from Duval County had been entered incorrectly, making Gore appear as if he had many more votes than he actually did. After fixing this error, the statistical models used by VNS and decision desks at all the networks showed the race could no longer be projected safely for either candidate. By 10:18 p.m., all the networks announced they were moving the state back to the undecided category, prompting Jeff Greenfield of CNN to quip, “Oh waiter, one order of crow.””

Of the 185,000 spoiled ballots in Florida, 113,000 were double and triple punched – and Gore’s name was punched on 75% of them. Almost 30,000 overpunched ballots were in Duval County which has a large black population. Could the spoiled ballots have been the cause of the Duval adjustments?

“At 2:15 a.m., Fox News called Florida and the presidency for Bush. Within five minutes, NBC, CNN, CBS, and ABC followed suit, announcing that Bush would be the forty-third president of the United States. Meanwhile, VNS and the AP chose not to call the race in Florida a second time, wary of the volatility in the data with the contest that close.”

“During the next couple hours, new errors were discovered. VNS had underestimated the number of votes remaining to be counted. Two counties—Volusia and Brevard—had mistakenly entered their vote totals in favor of Bush. Once these mistakes were corrected, the race narrowed considerably, so much so that Bush’s lead was inside the margin of error.”

What about the -16,022 Gore votes in Volusia? The media commentators called it a computer “glitch”. They always do. They never consider that it could have been the result of malicious coding.

“An embarrassment early in the evening had turned to a humiliation by the end, leading NBC News anchor Tom Brokaw to remark, “We don’t just have egg on our face; we have an omelet.”

“Despite the resulting indignation, the exit polls were not responsible for the erroneous second call. In fact, the exit polls were at that point no longer part of the estimation models, having been replaced by actual vote counts—incorrect as they were in some cases—over the course of the evening.”

Replaced by actual vote counts? That is what the perpetrators wanted to do all along. The media never reported that Gore won the unadjusted state exit polls by 50.8-44.5% (5.5 million votes) – way beyond the MoE. Or that he won the unadjusted National Exit Poll 48.5-46.2%, a 2.5 million margin. There were 5.4 million net uncounted votes. The True Vote Model indicates that he had 50.7%.

“However, the partisan skew in the measure of aggregate vote choice was higher than in previous elections. The preliminary data overstated the difference in the George W. Bush-John Kerry vote on election night by 5.5 percentage points, predicting a 51- to 48-percent advantage for Kerry rather than a 50.5- to 48-percent win for Bush.”

Kerry won the unadjusted state exit poll aggregate by 51.0-47.9%. He won the unadjusted National Exit Poll by 51.7-47.0%. The True Vote Model indicates that he had 53.5%.

“This was the highest error in the preliminary results since the 1992 election and double the error found in the previous two presidential elections. The discrepancy between the preliminary exit poll findings and the final election results was even greater in the competitive states. The exit polls predicted a Kerry victory in four states—Ohio, Iowa, New Mexico, and Nevada—in which Bush won, and overstated Kerry’s support by 11 percentage points in Ohio, 9 points in Pennsylvania, and 8 points in Florida.”

“Considering the closeness of the election, the exit polls seemed to suggest that Kerry was capable of winning the 2004 election. Political observers used these differences between the preliminary exit polls and the final results to support allegations of vote rigging and fraud in precincts deploying electronic voting machines, particularly in Ohio, where the state’s twenty-seven electoral votes, enough to change the winner of the Electoral College from Bush to Kerry, was decided by 118,775 ballots.”

The adjusted National Exit Poll indicated that there were 52.6 million returning Bush 2000 voters. But in the 2000 election, Bush had just 50.5 million recorded votes. He needed a 110% turnout of living Bush 2000 voters to match the 2004 recorded vote. Clearly a physical and mathematical impossibility.

“Steven Freeman of the University of Pennsylvania calculated the odds of the exit polls in Ohio, Pennsylvania, and Florida being as far off the final outcome as they were as 662,000 to 1.”

Note: The state exit poll margin of error (MoE) includes a 30% cluster factor.
In Pennsylvania, there were 2107 respondents (2.75%).
Kerry won the poll by 56.6-42.9%, an 800,000 vote margin.

In Ohio, there were 2020 respondents (2.82%).
Kerry won the poll by 54.1-45.7%, a 450,000 vote margin.

In Florida, there were 2862 respondents (2.38%).
Kerry won the poll by 50.8-48.2%, a 200,000 vote margin.

“The National Election Data Archive, a nonpartisan group of mathematicians and statisticians promoting election reform, found that twenty-two of the forty-nine precincts in Ohio polled by Edison/Mitofsky had reported Kerry vote share results that had less than a 5 percent chance of occurring, based on the state’s exit polls.”

“Rep. John Conyers, D-Mich., even used the exit polls as the basis for holding congressional hearings on vote irregularities in Ohio. Edison/Mitofsky disputed these charges in a follow-up report, contending that precincts with electronic voting had virtually the same rates of error as those using punch card systems.”

“They again attributed the bias to within-precinct error—error due to a systematic bias in the selection of voters within a precinct—and not to bias in the selection of precincts themselves. Bush voters were more likely to refuse to participate in the exit polls than Kerry voters. They hypothesized that the result was a function of the disproportionate numbers of interviewers under age thirty-five who administered the exit poll. Young people had more problems securing participation from voters than older respondents, perhaps because they were correctly perceived to have been more likely to have voted for Kerry.”

The same old discredited and debunked Reluctant Bush Responder canard that was refuted by the exit pollsters own data. It showed that exit poll response was highest in partisan Bush precincts – and in strong Republican states.

“Edison/Mitofsky also found that voting patterns within electoral groups were accurate once they were weighted to the official results. They found no evidence that the distribution of presidential vote choices within various demographic groups was biased, despite the vote choice of exit poll respondents overall overstating Democratic support.”

The “overstating” of 56 Kerry respondents for every 50 Bush respondents was not due to differential response; it was due to the fact that Kerry won the election with about 53% of the vote.

“Since 2004, less controversy has surrounded the exit polls. No serious technical problems have surfaced during the last three elections, enabling the media to prepare analyses of the outcome in a timely manner. Leaks of early wave findings have been contained. The preliminary exit polls have continued to overstate support for Democratic candidates; however, the final vote counts have had such large winning margins that the projected outcomes were no different.”

There was less controversy in 2008 only because Obama won by 9.5 million recorded votes. But the exit polls indicated that he won by nearly 23 million; the landslide was denied. The level of fraud was equivalent to 2004. Obama won the aggregate of the unadjusted state exit polls (82,388 respondents) by 58.0-40.5%. He won the unadjusted National Exit Poll (17,836 respondents) by 61-37%. He won the independent True Vote Model with 58.0%, exactly matching the state exit polls. He won the recorded vote by just 52.9-45.6%. How does one explain the massive discrepancy? It was surely not due to differential response.

Selection of Precincts
“National exit pollsters choose precincts by taking stratified probability samples in each of the states before drawing a national subsample from the state samples. This process involves sorting the precincts in each state into different categories or strata to guarantee that particular groups are represented adequately. To begin, precincts in each state are initially grouped into two strata according to their size to ensure the selection of smaller precincts.”

“Within each of these size strata, precincts are categorized by geographic region, usually between three to five regions in each state. For each state geographic region, precincts are ordered by their percentage vote for one of the major political parties in a previous election. Precincts are sampled from these strata with probabilities proportionate to the total votes cast in them in a prior election, so that every precinct has as many chances of being picked by pollsters as it has voters. The samples drawn in each state are then combined, and a national sample of precincts is selected from them using a previous presidential race to determine the relative number of precincts chosen from each state.”

Sampling voters in proportion to the recorded vote in prior elections is a persistent source of bias, since the recorded votes were fraudulent and favored the Republicans. So the sampled exit polled precincts were over-weighted for the GOP.

“Typically, the total number of precincts selected in the national exit poll is between 250 and 300. Ultimately, the number of precincts chosen represents a tradeoff between sampling error and financial constraints. Research by Edison/Mitofsky has shown that the number of precincts selected has not been responsible for the Democratic overstatements that have continually appeared in the exit polls.”

“For example, they found that for the 2004 election the actual distribution of the presidential vote in the precincts used in the exit poll samples did not differ significantly from the actual vote distribution nationwide. In fact, these precincts overstated support for the Republican candidate, George W. Bush, but only by 0.4 points, on average, across the states.”

Mitofsky believed that the exit poll precinct samples were perfect. But he also believed that 56 Democrats responded for every 50 Republicans – even though his own data indicates that response rates were higher in partisan Bush precincts.

“Refusal rates, or for that matter miss rates, are not necessarily problematic, as long as the propensity of different groups to participate does not vary. However, if one group is more or less likely than other groups to complete exit surveys, their responses will be over or under-represented, thereby biasing estimates for the overall electorate. For example, the partisan overstatement repeatedly found in the national exit polls over the past several decades appears to be due to the greater willingness of Democratic voters to complete the exit polls, compared with their Republican counterparts. However, once this discrepancy has been corrected by weighting the exit polls to correspond with the actual vote, there has been no evidence that the vote estimates within groups are biased.”

Greater Democratic willingness to be exit polled is a myth -not a fact. The exit pollsters own data shows otherwise. In 2000, 2004 and 2008, Republican exit poll shares and vote shares were positively correlated (.25) to state exit poll response. Bush vote shares increased as response rates increased, refuting the Reluctant Republican Responder hypothesis.

“National exit pollsters account for early/absentee voting by conducting telephone surveys in states where the rates of early voting are highest. VNS first incorporated early/absentee voting in 1996, surveying voters in California, Oregon, Texas, and Washington. By 2008, NEP was conducting telephone surveys in eighteen states, including Oregon, Washington, and Colorado, where the proportions of early voting were so high that no in-person exit polls were conducted on election day.”

Early voting data in the 2008 election indicates that Oregon, Washington, and Colorado had the lowest red-shifts. Was it just a coincidence that the states with the highest early voting rates were the ones which most closely matched the unadjusted exit polls?

Take the Election Fraud Probability 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

 

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

2004 Election Model Graphs
State aggregate poll trend
Electoral vote and win probability
Electoral and popular vote
Undecided voter allocation impact on electoral vote and win probability
National poll trend
Monte Carlo Simulation
Monte Carlo Electoral Vote Histogram

2006 Midterms
Democratic Generic 120-Poll Trend Model: 56.4-41.6%
Unadjusted National Exit Poll: 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

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

2010 Midterms Overview
True Vote Model Analysis

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

2012 Model Overview
Electoral Vote Trend
Monte Carlo Simulation Electoral Vote Frequency Distribution

 

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

 

Unadjusted 2008 State Exit Polls: Further Confirmation of the True Vote Model

Richard Charnin (TruthIsAll)

Sept. 20, 2011

It is instructive to see how the unadjusted 2008 exit polls polls compare to the recorded vote and the True Vote Model (TVM). The basic results are not surprising: Obama did better in the aggregate state exit polls (58.1%) than the vote count (52.9%). But the Democrats always do better in the polls. What is surprising is that he did 5.2% better – exactly matching the TVM. By way of comparison, Kerry did 3.7% better in the unadjusted exit polls (52%) than in the recorded vote (48.3%). He had 53.6% in the TVM.

A Triple Confirmation

In the 2008 National Exit Poll (NEP), 4178 of the 17836 responders were asked how they voted in 2004: 1815 (43.4%) said they were Kerry voters, 1614 (38.6%) Bush, 188 (4.5%) third-party and 561 (13.4%) did not vote. Applying Final 2008 NEP vote shares to the returning voter mix, Obama had a 58.1% share – exactly matching a) his 58.1% share of the aggregate unadjusted state exit polls and b) his 58.1% TVM share! The returning voter mix implied that Kerry won by 50.2-44.6%.

But all exit polls are forced to match the recorded vote. The pollsters needed an impossible 46/37% Bush/Kerry mix which implied that Bush won by 52.6-42.3%. His (bogus) recorded margin was 50.7-48.3%. Kerry won the True Vote with 53.6% (Table 6). In the Final 2008 NEP, pollsters effectively converted 269 of 1815 (15%) Kerry responders to Bush responders in order to force a match to the recorded vote.

To summarize, the unadjusted 2008 NEP exactly matched the weighted aggregate share of the unadjusted state exit polls, based on how the the exit poll responders said they voted in 2004 and 2008. It also matched the TVM which used 2004 votes cast, voter mortality, a best estimate of living 2004 voter turnout in 2008 – and the Final 2008 NEP vote shares. Obama had 58.1% in each calculation – a triple confirmation that Obama won a 23 million vote landslide, far exceeding his 9.5 million recorded vote margin.

But that’s not all. The National Exit Poll of 17836 respondents is a subset of the 80,000 sampled in the state exit polls. Obama won the unadjusted National Exit Poll by 61-37%, a landslide of historic proportions. However, the state exit polls have a smaller margin of error and are probably a better estimate of the True Vote.

This graph shows that Obama’s 58% True Vote share is confirmed by three independent statistical measures: 1) Unadjusted National Exit Poll, 2) Unadjusted state exit polls, 3) and 10 million late (paper ballot) votes.

The key result is the state exit poll aggregate vote share. The national sample size was approximately 80,000. The average state exit poll margin of error was 3.35% (including a 30% “cluster” effect). The margin of error was exceeded in 37 states; in 2004 it was exceeded in 29. Of the 50 states and DC, 45 shifted to McCain from the exit poll. The difference in margin between the exit poll and the recorded vote is the average Within Precinct Discrepancy (WPD). The WPD was 10.6 in 2008, far above the 7.4 in 2004.

The True Vote Model has closely matched the unadjusted state and national exit polls in every presidential election since 1988. In the 11 presidential elections from 1968 to 2008, the Republicans had a 49-45% recorded vote margin while the Democrats had a 49-45% True Vote margin.

In a given state, the exit poll varies from the corresponding True Vote calculation. But the total aggregate share is an exact match, illustrating the Law of Large Numbers and the Central Limit Theorem.

The National True Vote Model is based on previous election votes cast and turnout of previous election voters, current votes cast and National Exit Poll (NEP) vote shares. The State Model works the same way. It’s based on returning state voters with NEP vote shares adjusted according to the state/national vote share ratio.

It should be obvious by now that final weighting adjustments made to the exit polls are made to match the recorded vote. In 2004, in addition to the impossible return voter mix, the 12:22am preliminary national exit poll vote shares had to be adjusted in the Final NEP. The required turnout of living Bush voters was 110%. Kerry had a 52.0% aggregate share and a 53.6% TVM share. Of course, all demographic categories had to be adjusted to match the vote count: Final NEP “Party-ID”, “When Decided” and “Bush Approval” crosstab weights did not match the corresponding pre-election polls and were adjusted to force a match to the recorded vote.

 

Footprints of Systemic Election Fraud: 1988-2008 State Exit Poll Discrepancies

Richard Charnin (TruthIsAll)

Updated: Sept.9, 2012

This is an updated analysis of state and national exit poll discrepancies in the 1988-2008 presidential elections. The unadjusted data has made available on the Roper Center for Public Opinion (UConn) website. Now we know what the respondents actually said as to how they voted – fundamental information that was not previously available. It is not the raw precinct level data that analysts would love to see and which the corporate media (the National Election Pool) will not release.

Nevertheless, the unadjusted state and national exit poll data is the mother-lode for SERIOUS exit poll analysis. The pattern is clear: the Democrats always do better in the polls than in the recorded count. There is no evidence that this one-sided result is due to anything other than vote miscounts.

Each presidential election consists of 50 state exit poll files (and Washington DC) in PDF format. In order to utilize the data for a meaningful analysis, it had to be re-organized and consolidated in a single workbook. The workbook contains individual worksheets for each election, as well as other sheets for relevant graphs and tables.

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

It has long been established that Final National Exit Polls are always forced to match the recorded vote, often with impossible returning voter weights. The unadjusted data shows just how the exit pollsters had to adjust the actual responses to force the match. Furthermore, and most important, it confirms True Vote Model calculations in each election. The pattern of massive discrepancies totally confirm that the adjusted Final National Election Poll is fiction and debunks the corresponding myth that elections are fair and that the votes are counted accurately.

The original post was based on 1988-2004 data from the Edison/Mitofsky 2004 Election Evaluation Report.

1988-2008 Unadjusted Exit Polls

According to the unadjusted state and national exit polls and the True Vote Model, the Democrats won the 1988-2008 popular vote by a far bigger margin than the recorded vote indicates.

1988-2008 Average National Presidential Vote Shares
....Measure........Dem...Rep...Margin....Note
1) Recorded : 47.9-45.9% (2.0%) - Vote count
2) WPE / IMS : 50.8-43.1% (7.7%) - Edison-Mitofsky
3) State Exit : 51.8-41.6% (10.2%) - Roper
4) National Exit: 51.7-41.7% (10.0%) - Roper
5) True Vote 1 : 50.2-43.8% (6.4%) - previous recorded vote
6) True Vote 2 : 51.6-42.5% (9.1%) - previous votes cast
7) True Vote 3 : 52.5-41.5% (11.0%) - previous unadjusted exit poll
8) True Vote 4 : 53.0-41.0% (12.0%) - previous True Vote


1988-2008: 274 STATE EXIT POLLS

PROOF OF SYSTEMIC ELECTION FRAUD BEYOND ANY DOUBT

This table illustrates the one-sided red-shift from the Democrat in the state exit polls to the Republican in the recorded vote. The margin of error includes a 30% cluster effect. The MoE was exceeded in an astounding 126 of 274 state presidential exit polls from 1988-2008. The probability is ZERO. At the 95% confidence level, we would expect 14 polls to exceed the MoE. Of the 126 elections, 123 red-shifted to the GOP and just 3 to the Democrat. The probability is 5.4E-106 – ZERO.

State Exit Poll Margin of Error

......................Total..1988...1992..1996..2000..2004..2008
....................... 3.26% 3.34% 3.42% 3.07% 3.64% 3.11% 2.97%
Exit Polls:
red-shift to GOP........226 20 44 43 34 40 45
exceeding MoE...........126 11 26 16 13 23 37
exceeding MoE (GOP).....123 11 26 16 12 22 36

Probability of..........Average.1988.....1992....1996....2000....2004....2008
126 exceeding MoE.......8.0E-75 6.6E-09 2.1E-15 1.5E-09 7.5E-07 2.1E-15 2.1E-15
123 exceeding MoE (GOP).5.E-106 5.0E-11 2.4E-25 4.8E-13 8.7E-09 3.5E-20 2.4E-39
226 red-shift to GOP....3.7E-31 7.7E-04 1.6E-08 1.0E-07 7.7E-03 1.2E-05 2.1E-09

States in which the Democrats won the exit poll and lost the vote

1988: CA IL MD MI NM PA VT 
Dukakis had a 51-47% edge in 24 battleground state polls.
He lost by 7 million votes,

1992: AK AL AZ FL IN MS NC OK TX VA 
Clnton had a 18 million vote margin in the state exit polls.
He won the the recorded vote by just 6 million.

1996: AK AL CO GA ID IN MS MT NC ND SC SD VA 
Clinton had a 16 million vote margin in the state exit polls.
He won by just 8 million recorded votes.

2000: AL AR AZ CO FL GA MO NC NV TN TX VA 
Gore needed just ONE of these states to win the election.
He won the state exit polls by 6 million, matching the TVM. 

2004: CO FL IA MO NM NV OH VA
Kerry needed FL or OH to win. He won the national and state exit polls by 5-6 million with 51-52%. He won the TVM by 10 million with 53.6%.

2008: AL AK AZ GA MO MT NE 
Obama had 58% in the state exit polls (exact match to the TVM), a 23 million margin (9.5 recorded) and 61% in the unadjusted National Exit Poll.

In 1988, Dukakis won the unadjusted National Exit Poll (11,586 respondents) by 49.8-49.2%. He won the exit polls in the battleground states by 51.6-47.3%. There were 11 million uncounted votes, an indicator that Dukakis may have won since 70-80% of uncounted votes are Democratic. But he lost by 7 million recorded votes (53.4-45.6%).

In 1992, Clinton won the unadjusted state exit polls (54,000 respondents) by 18 million votes (47.6-31.7%). He won the unadjusted National Exit Poll (15,000 respondents)by 46.3-33.4%. He had 51% in the True Vote Model (TVM). But his recorded margin was just 5.6 million (43.0-37.5%). The Final National Exit Poll (NEP) was forced to match the recorded vote. The NEP implied that there was a 119% turnout of living 1988 Bush voters. There were 10 million uncounted votes. The landslide was denied.

In 1996, Clinton won the unadjusted exit polls (70,000 respondents) by 16 million votes (52.6-37.1%). He had 53.6% in the TVM. His recorded margin was 8 million (49.2-40.8%). The Final National Exit Poll (NEP) was forced to match the recorded vote. There were 10 million uncounted votes. The landslide was denied.

In 2000, Gore won the unadjusted state exit polls (58,000 respondents) by 6 million votes (50.8-44.4%). He had 51.5% in the TVM. But he won the recorded vote by just 540,000. There were 6 million uncounted votes. The election was stolen.

In 2004, Kerry won the unadjusted state exit poll aggregate (76,000 respondents) by 51.1-47.5%. He won the unadjusted National Exit Poll (13,660 respondents) by 51.7-47.0%, a 6 million vote margin. He had 53.6% (a 10 million margin) in the True Vote Model But he lost by 3.0 million recorded votes. There were 4 million uncounted votes. The election was stolen.

In 2008, Obama won the unadjusted state exit poll aggregate (83,000 respondents) by 58.1-40.3%, a 23 million vote margin – a near-exact match to the TVM. He won the unadjusted National Exit Poll (17,836 respondents) by a whopping 61-37%. Officially, he had 52.9% and won by 9.5 million votes. The landslide was denied.

http://richardcharnin.wordpress.com/2011/11/13/1988-2008-unadjusted-state-exit-polls-statistical-reference/

___________________________________________________________________________

http://richardcharnin.com/StateExitPollDiscrepancies.htm

The full set of 2008 exit polls and 24 of the 1988 state polls are from the Roper website. The analysis is displayed in the following 12 data tables:

1988-2008
1 State Exit Poll Discrepancies

1988
2 True Vote Model vs. Final National Exit Poll
3 Battleground Exit Polls vs. Recorded Vote

2004
4 National Exit Poll
5 True Vote Model
6 Sensitivity Analysis
7 State Recorded, Exit Poll, True Vote Shares, 8 State Exit Poll Timeline

2008
9 National Exit Poll
10 True Vote Model
11 Unadjusted State exit polls vs. Recorded Vote and True Vote
12 Unadjusted National Exit Poll vs. Final

Within Precinct Error (WPE) is the difference between the unadjusted exit poll and recorded vote margins. “Error” implies that the exit polls were wrong and the election was fraud-free. But millions of votes are uncounted in every election (nearly 11 million in 1988 and 4 million in 2004). Therefore, it is more accurate to refer to Within Precinct Discrepancy (WPD). A positive WPD indicates that the vote shift favored the GOP; a negative WPD favored the Democrat. In 2004, Kerry won the state exit polls by 52-47% but lost the recorded vote by 50.7-48.3%, a WPD of 7.4%.

In the 274 state elections which were exit polled, 226 shifted from the exit poll to the Republican and 48 shifted to the Democrat. The one-sided red-shift to the Republican implies that the exit polls were incorrect or the votes were miscounted. It could not have been due to chance. Exit polls are known to be quite accurate – outside the USA.

Were the discrepancies due to Republican voter reluctance to be polled in each of the six elections? Not likely. Were they due to Democratic voters misstating how they voted to the exit pollsters in each of the six elections? Not likely. Or were they due to the millions of mostly Democratic votes that were uncounted? That is more than likely. It is a fact.Were they due to votes that were miscounted in favor of the Republican? That is quite likely.

- In 15 Democratic states, the average WPD was 6.3. The MoE was exceeded in 41 state elections. All shifted in favor of the Republicans.
- In 15 Battleground states, the average WPD was 5.0. The MoE was exceeded in 37. All shifted in favor of the Republicans
- In 21 Republican states, the average WPD was 3.7. The MoE was exceeded in 35. All but two shifted in favor of the Republicans.

Given a 95% level of confidence, approximately 14 of 274 elections would be expected to fall outside the margin of error. The probability that the MoE would be exceeded in a state is 5%. But the MoE was exceeded in 126 elections, all but threein favor of the Republicans. The probability is ZERO that this was due to chance.

1988
The 1988 CBS exit poll indicate that Dukakis did substantially better than the Edison/Mitofsky report. They show Dukakis winning the 24 battleground state aggregate by a solid 51.6-47.3%. But George H.W. Bush won the recorded vote by 53.4-45.6%. There were 68.7 million recorded votes in the battleground states (75% of the 91.6 million recorded). Seven of the 24 flipped to Bush from the exit polls – a total of 132 electoral votes: CA, MD, PA, MI, IL, VT and NM. The margin of error was exceeded in 11 of the 24 states. Dukakis may very well have won the election. According to the Census, there were at least 10.6 million net uncounted votes (i.e. net of stuffed ballots).

Dukakis won the Roper California exit poll in a landslide (57.7-40.8%), yet Bush won the recorded vote (51.1-47.7%) – an amazing 20.4% discrepancy. He won the IL exit poll by 8% but lost by 2%. In MI, Dukakis had a 3.5% exit poll margin and lost by 8%. In MD, his 12% exit poll win morphed into a 3% defeat. In PA, he won the exit poll by less than 1% and lost by 3%. In Bush’s home state of Texas, he barely edged Dukakis by 1% in the exit poll. He won the state by 13%.

1988 Battleground State Exit Polls
http://richardcharnin.com/1988RoperExit_16115_image001.gif

2004
- In 15 strong Democratic states, the average WPD was 8.9.
The MoE was exceeded in 11 states (73%) – all shifted to Bush.
- In 15 Battleground states, the average WPD was 6.9.
The MoE was exceeded in 10 states (67%) – all shifted to Bush.
- In 21 Republican states, the average WPD was 3.8.
The MoE was exceeded in 7 states (33%) – all shifted to Bush.

The margin of error was exceeded in a total of 23 states – all but one in favor of Bush. The probability is 1 in 19 trillion that the MoE would be exceeded in 16 states. Imagine what the probability is for 28 states. Assuming a 2% MoE, the probability is even lower since the MoE was exceeded in 36 states: 34 in favor of Bush, 2 in favor of Kerry.

The distribution of the WPD in Democratic, GOP and Battleground states indicates that the GOP strategy was:
1) Pad Bush’s popular vote “mandate” by cutting Democratic margins in heavily populated BLUE states (NY, CA, CT, NJ, MD, MA, MI).
2) Steal the electoral votes in Battleground states (FL, OH, NM, CO, NV, MO, IA).
3) Pad the vote in RED states with large minority (Democratic) voting blocs (TX, MS, AL, TN, SC). Ignore the others (ND, SD, OK, MT, KY)

2008
The exit poll discrepancies (10.6 WPD) were substantially greater than in other elections. The True Vote Model (TVM) exactly matched Obama’s 58% aggregate share of the unadjusted state exit polls – a 23 million vote margin. McCain’s recorded share exceeded his exit poll in 45 states. The exit poll margin of error was exceeded in 37 states, all but one in favor ofr McCain. Obama won by nearly 23 million True votes; he won officially by 9.5 million.

2008 Unadjusted State Exit Polls confirm the True Vote Model:
http://richardcharnin.com/2008ExiPollConfirmationTVM.htm

This graph tells you all you need to know about the 2008 election. Obama had a 58% True Vote share – not the official recorded 53%. This is confirmed by at least 4 independent statistical measures: 1) Unadjusted National Exit Poll, 2) Unadjusted state exit polls, 3) True Vote Model and 4)10 million late (paper ballot) votes.

http://richardcharnin.com/2008NEPUnadjustedRoper_28080_image001.gif

 

Monte Carlo Simulation: Election Forecasting and Exit Poll Modeling

Richard Charnin

Updated: July 8, 2012

2004 Monte Carlo Electoral Vote Simulation (pre-election and  exit polls)

The simulation model consists of 200 election trials based on pre-election state polls and post-election exit polls. It is strong circumstantial evidence that the election was stolen.

In the pre-election model, the state and national polls are adjusted for the allocation of undecided voters. The post-election model is based on unadjusted and adjusted state exit polls. Monte Carlo simulation is used to project state and aggregate vote shares and calculate the popular and electoral vote win probabilities.

The state win probability is a function of 1) the projected vote shares (after allocating undecided voters) and 2) the state poll margin of error.

The expected (theoretical) electoral vote can be calculated using a simple summation formula. It is just the product sum of the state win probabilities and corresponding electoral votes.

The purpose of the simulation is to calculate the overall probability of winning the electoral vote. As the number of election trials increase, the average (mean) electoral vote will approach the theoretical expected value.

The electoral vote win probability is the ratio of the number of winning election trials to the total number of trials.

In every presidential election, millions of voters are disenfranchised and millions of votes are uncounted. Forecasting models should have the following disclaimer:

Note: The following forecast will surely deviate from the official recorded vote. If they are nearly equal, then there must have been errors in the a) input data, b) assumptions, c) model logic and/or methodology.

Kerry led the weighted pre-election state and national polls by 1%. After allocating 75% of undecided voters to him, he was projected to win by 51.4-47.7%. Kerry had 51.1% in the unadjusted state exit poll aggregate (76,000 respondents) and 51.7% in the unadjusted National Exit Poll (13,660 respondents).

The National Election Pool, a consortium of six media giants, funds the exit polls. The published National Exit Poll is always forced to match the recorded vote. The Final 2004 NEP adjusted the actual exit poll responses to force a match to the recorded vote (Bush by 50.7-48.3%).

The large discrepancy between the exit polls and the vote count indicates that either a) the pre-election and unadjusted exit polls were faulty or b) the votes were miscounted, or c) a combination of both. Other evidence confirms that the votes were miscounted in favor of Bush.

The True Vote always differs from the official recorded vote due to uncounted, switched and stuffed ballots. Were the pollsters who forecast a Bush win correct? Or were Zogby and Harris correct in projecting that Kerry would win?

None of the pollsters mentioned the election fraud factor – the most important variable of all.

MODEL OVERVIEW

The workbook contains a full analysis of the 2004 election, based on four sets of polls:

(1) Pre-election state polls
(2) Pre-election national polls
(3) Post-election state exit polls
(4) National Exit Poll

Click the tabs at the bottom of the screen to select:
MAIN: Data input and summary analysis.
SIMULATION: Monte Carlo Simulation of state pre-election and exit polls.
NATPRE: Projections and analysis of 18 national pre-election polls.
In addition, three summary graphs are provided in separate sheets.

Calculation methods and assumptions are entered in the MAIN sheet:
1) Calculation code: 1 for pre-election polls; 2 for EXIT polls.
2) Undecided voter allocation (UVA): Kerry’s share (default 75%).
3) Exit Poll Cluster Effect: increase in margin of error (default 30%).
4) State Exit Poll Calculation Method:
1= WPD: average precinct discrepancy.
2= Best GEO: adjusted based on recorded vote geographic weightings.
3= Composite: further adjustment to include pre-election polls.
4= Unadjusted state exit polls

Note: The Composite state exit poll data set (12:40am) was downloaded from the CNN election site by Jonathan Simon. The polls were in the process of being adjusted to the incoming vote counts and weighted to include pre-election polls.The final adjustment at 1am forced a match to the final recorded votes.

2004 ELECTION MODEL

The Election Model was executed weekly from August to the election. It tracked state and national polls which were input to a 5000 trial Monte Carlo simulation. The final Nov. 1 forecast had Kerry winning 51.8% of the two-party vote and 337 electoral votes> He had a 99.8% electoral vote win probability: the percentage of trials in which he had at least 270 electoral votes.

Simulation forecast trends are displayed in the following graphs:

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

POLL SAMPLE-SIZE AND MARGIN OF ERROR

Approximately 600 were surveyed in each of the state pre-election polls (a 4% margin of error). The national aggregate has a lower MoE; approximately 30,000 were polled. In 18 national pre-election polls, the samples ranged from 800 (3.5% MoE) to 3500 (1.7% MoE).

In the exit polls, 76,000 voters were sampled. Kerry won the unadjusted state exit poll aggregate by 51.1-47.5%. He also won the unadjusted National Exit Poll (NEP) by 51.7-47.0%. The NEP is a 13,660 sample subset of the state exit polls.The NEP was adjusted to match the recorded vote -using the same 13660 respondents.

Assuming a 30% exit poll “cluster effect” (1.1% MoE), Kerry had a 98% probability of winning the popular vote. The Monte Carlo simulation indicates he had better than a 99% probability of winning the Electoral Vote.

The “cluster effect” is the percentage increase in the theoretical Exit Poll margin of error. When it is not practical to carry out a pure random sample, a common shortcut is to use an area cluster sample: primary Sampling Units (PSUs) are selected at random within the larger geographic area.

The Margin of Error (MoE) is a function of the sample size (n) and the polling percentage split: MoE = 1.96* Sqrt(P*(1-P)/n)

ELECTION FORECASTING METHODOLOGY

The Law of Large Numbers is the basis for statistical sampling. All things being equal, polling accuracy is directly related to sample size – the larger the sample, the smaller the margin of error (MoE). In an unbiased random sample, there is a 95% probability that the vote will fall within the MoE of the mean.

There are two basic methods used to forecast presidential elections:
1) Projections based on state and national polls
2) Time-series regression models

Academics and political scientists create multiple regression models to forecast election vote shares and run the models months in advance of the election. The models utilize time-series data, such as: economic growth, inflation, job growth, interest rates, foreign policy, historical election results, incumbency, approval rating, etc. Regression modeling is an interesting theoretical exercise, but it does not account for daily events which affect voter psychology.

Polling and regression models are analogous to the market value of a stock and its intrinsic (theoretical) value. The latest poll share is the equivalent of the current stock price. The intrinsic value of a stock is based on forecast cash flows. The intrinsic value is rarely equal to the market value.

The historical evidence is clear: state and national polls, adjusted for undecided voters and estimated turnout, are superior to time-series models executed months in advance.

Inherent problems exist in election models, the most important of which is never discussed: Election forecasters and media pundits never account for the probability of fraud. The implicit assumption is that the official recorded vote will accurately reflect the True Vote and that the election will be fraud-free.

MONTE CARLO SIMULATION

Monte Carlo is a random process of repeated experimental “trials” applied to a mathematical system model. The Election Simulation Model runs 200 trial “elections” to determine the expected electoral vote and win probability.

Statistical polling (state and national) ideally is an indicator of current voter preference. Pre-election poll shares are adjusted for undecided voters and state win probabilities are calculated. The probabilities are input to a Monte Carlo simulation based on random numbers. The final probability of winning the electoral vote is simply the number of winning election trials divided by the total number of trials (200 in the ESM; 5000 in the Election Model).

The only forecast assumption is the allocation of undecided/other voters. Historically, 70-80% of undecided voters break for the challenger. If the race is tied at 45-45, a 60-40% split of undecided voters results in a 51-49% projected vote share.

ELECTORAL AND POPULAR VOTE WIN PROBABILITIES

The theoretical expected electoral vote for a candidate is a simple calculation. It is just the sum of the 51 products: state electoral vote times the win probability. In the simulation, the average (mean) value will converge to the theoretical value as the number of election trial increase.

The probability of winning the popular vote is a function of the projected 2-party vote share and polling margin of error. These are input to the Excel normal distribution function. The simulation generates a electoral vote win probability that is not sensitive to minor changes in the state polls.

Prob (win) = NORMDIST (P, 0.50, MoE/1.96, True)

For each state in an election trial, a random number (RND) between 0 and 1 is generated and compared to the probability of winning the state. For example, if Kerry has a 90% probability of winning Oregon and RND is less than 0.90, Kerry wins 7 electoral votes. Otherwise, if RND is greater than 0.90, Bush wins. The procedure is repeated for all 50 states and DC. The election trial winner has at least 270 EV.

The electoral vote win probability is directly correlated to the probability of winning the national popular vote. But electoral vote win probabilities in models developed by academics and bloggers are often incompatible with the projected national vote shares.

For example, assume a 53% projected national vote share. If the corresponding EV win probability is given 88%, the model design/logic is incorrect; the 53% share and 88% win probability are incompatible. For a 53% share, the win probability is virtually 100%. This is proved using Monte Carlo simulation based on state win probabilities in which there is a 53% aggregate projected national share.

The state win probability is based on the final pre-election polls which typically sample 600 likely voters (a 4% MoE). In the 2004 Election Simulation Model, the electoral vote is calculated using 200 election trials. The average (mean) electoral vote is usually within a few votes of the median (middle value). As the number of simulation trials increase, the mean approaches the theoretical expected value. That is due to the Law of Large Numbers.

SENSITIVITY ANALYSIS

A major advantage of the Monte Carlo Simulation method is that the win probability is not sensitive to minor deviations in the state polls. It is not an all-or-nothing proposition as far as allocating the electoral vote is concerned. A projected 51% vote share has less electoral “weight” than a 52% share, etc. Electoral vote projections from media pundits and Internet bloggers use a single snapshot of the latest polls to determine a projected electoral vote split. This can be misleading when the states are competitive and often results in wild electoral vote swings.

In the Election Model, five projection scenarios over a range of undecided voter allocation assumptions display the effects on aggregate vote share, electoral vote and win probability.

Snapshot projections do not provide a robust expected electoral vote split and win probability. That’s because unlike the Monte Carlo method, they fail to consider the two bedrocks of statistical analysis: The Law of Large Numbers and the Central Limit Theorem.

For example, assume that Florida’s polls shift 1% from 46-45 to 45-46. This would have a major impact in the electoral vote split. On the other hand, in a Monte Carlo simulation, the change would have just a minimal effect on the expected (average) electoral vote and win probability. The 46-45 poll split means that the race is too close to clearly project a winner; both candidates have a nearly equal win probability.

NORMAL DISTRIBUTION

The Excel function has a very wide range of applications in statistics, including hypothesis testing.

NORMDIST (x, mean, stdev, cumulative)
X is the value for which you want the distribution.
Mean is the arithmetic mean of the distribution.
Stdev is the standard deviation of the distribution.

EXAMPLE: Calculate the probability Kerry would win Ohio based on the exit poll assuming a 95% level of confidence.
Sample Size = 1963; MoE =2.21%; Cluster effect = 20%; Adj. MoE = 2.65%
Std Dev = 1.35% = 2.65% / 1.96

Kerry win probability:
Kerry = 54.0%; Bush = 45.5%; StdDev = 1.35%
Kerry 2-party share: 54.25%
Probability = NORMDIST(.5425, .5, .0135, TRUE)= 99.92%

BINOMIAL DISTRIBUTION

BINOMDIST is used in problems with a fixed number of tests or trials, where the outcome of any trial is success or failure. The trials are independent. The probability of success is constant in each trial (heads or tails, win or lose).

EXAMPLE: Determine the probability that the state exit poll MoE is exceeded in at least n states assuming a 95% level of confidence. The one-tail probability of Bush exceeding his exit poll share by the MoE is 2.5%. Therefore the probability that at most N-1 states fall within the MoE is:
Prob = BINOMDIST (N-1, 50, P, TRUE)
N = 16 states exceeded the MoE at 12:22am in favor of Bush.
The probability that the MoE is exceeded in at least 16 exit polls for Bush:
= 1- BINOMDIST (15, 50, 0.025, TRUE)
= 5.24E-14 or 1 in 19,083,049,268,519

A SAMPLING PRIMER

The following is an edited summary from http://www.csupomona.edu/~jlkorey/POWERMUTT/Topics/data_collection.html

A random sample is one which each outcome has an equal probability of being included. It is an unbiased estimate of the characteristics of the population in which the respondents are representative of the population as a whole.

The reliability of the sample increases with the size of the sample. Ninety-five times out of a hundred, a random sample of 1,000 will be accurate to within about 3 percentage points. The sample has a margin of error of approximately plus or minus (±) 3 percent at a 95 percent confidence level. If a random sample of 1,000 voters shows that 60 percent favor candidate X, there is a 95 percent chance that the real figure in the population is in the 57 to 63 percent range.

Beyond a certain point, the size of the population makes little difference. The confidence interval is not reduced dramatically. Therefore pre-election national polls usually don’t survey more than about 1,500 respondents. Increasing this number increases the cost proportionately, but the margin of error will be reduced only a little.

Often it is not practical to carry out a pure random sample. One common shortcut is the area cluster sample. In this approach, a number of Primary Sampling Units (PSUs) are selected at random within a larger geographic area. For example, a study of the United States might begin by choosing a subset of congressional districts. Within each PSU, smaller areas may be selected in several stages down to the individual household. Within each household, an individual respondent is then chosen. Ideally, each stage of the process is carried out at random. Even when this is done, the resulting sampling error will tend to be a little higher than in a pure random sample,[7] but the cost savings may make the trade-off well worthwhile.

Somewhat similar to a cluster sample is a stratified sample. An area cluster sample is appropriate when it would be impractical to conduct a random sample over the entire population being studied. A stratified sample is appropriate when it is important to ensure inclusion in the sample of sufficient numbers of respondents within subcategories of the population.

Even in the best designed surveys, strict random sampling is a goal that can almost never be fully achieved under real world conditions, resulting in non-random (or “systematic”) error. For example, assume a survey is being conducted by phone. Not everyone has one. Not all are home when called. People may refuse to participate. The resulting sample of people who are willing and able to participate may differ in systematic ways from other potential respondents.

Apart from non-randomness of samples, there are other sources of systematic error in surveys. Slight differences in question wording may produce large differences in how questions are answered. The order in which questions are asked may influence responses. Respondents may lie.

Journalists who use polls to measure the “horse race” aspect of a political campaign face additional problems. One is trying to guess which respondents will actually turn out to vote. Pollsters have devised various methods for isolating the responses of “likely voters,” but these are basically educated guesses. Exit polls, in which voters are questioned as they leave the voting area, avoid this problem, but the widespread use of absentee voting in many states creates new problems. These issues are usually not a problem for academic survey research. Such surveys are not designed to predict future events, but to analyze existing patterns. Some are conducted after the election. The American National Election Study, for example, includes both pre and post election interviews. Post election surveys are not without their own pitfalls, however. Respondents will sometimes have a tendency to report voting for the winner, even when they did not.

The American National Election Study split its sample between face to face and telephone interviews for its 2000 pre-election survey. The response rate was 64.8 percent for the former, compared to 57.2 percent for the latter. An analysis of a number of telephone and face-to-face surveys showed that face-to-face surveys were generally more representative of the demographic characteristics of the general population. Note that many telephone surveys produce response rates far lower than that obtained by the ANES.

Another approach is the online poll, in which the “interaction” is conducted over the Internet. Like robo polls, online polls are also less expensive than traditional telephone surveys, and so larger samples are feasible. Because they require respondents to “opt in,” however, the results are not really random samples.

When samples, however obtained, differ from known characteristics of the population (for example, by comparing the sample to recent census figures), samples can be weighted to compensate for under or over representation of certain groups. There is still no way of knowing, however, whether respondents and non-respondents within these groups differ in their political attitudes and behavior.