Tag Archives: Wisconsin recalls

The Exit Poll Smoking Gun: “How did you vote in the last election”?

Richard Charnin
Nov. 19, 2014
Updated Sept.30, 2015

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

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

The Exit Poll Smoking Gun: “How did you vote in the last election”?

This question has proven to be devastating for those who still believe there is no such thing as election fraud. So devastating, it was not asked in the 2012 presidential exit poll or the 2014 House exit poll.

The exit pollsters freely admit that they adjust the polls to match the recorded vote. The rationale is that since the exit polls are always off by an 8% average margin, they must be adjusted to match the pristine, fraud-free recorded vote. The pollsters never consider the possibility that the unadjusted exit polls were accurate; they claim that the discrepancies are due to consistently bad polling.

So why do the pollsters get paid the big bucks from the National Election Pool? In any other profession, if your analysis is way off, you had better get it right the next time. If it’s way off on your second try, you get one more chance. If you fail a third time, that’s it. Someone else gets your job. But here’s the catch: the pollsters were accurate; the unadjusted polls matched the True Vote. So why did they have to adjust the polls to match the bogus recorded vote?

The unadjusted exit polls were forced to match the recorded vote in every presidential election since 1988. The Democrats won the state and national exit polls by 52-42%, but won the the recorded vote by just 48-46%. The probability of the discrepancy: 1 in trillions. The exit polls were right. The vote counts were wrong. It’s as simple as that.

Does the rationale sound crazy to you? Despite all of the anecdotal evidence of election fraud, it is never considered by the corporate media (the National Election Pool) who fund the exit pollsters.

This graph shows that in the 1972, 1988, 1992, 2004 and 2008 presidential elections, the National Exit Poll was forced to claim there was over 100% turnout of living Nixon, Bush1 and Bush2 voters from the prior election. Impossible – and proof of fraud.

I have been posting on this very unscientific procedure since 2004. In this post I will review the basic method used to match the vote: changing the mix of returning voters. We will look at the 2004-2008 presidential elections and the 2010-2014 Wisconsin and Florida governor elections. The pattern of deceit will be revealed by adjustments made to the number of exit poll respondents and returning voters to match the official recorded vote counts – and cover up the fraud.

2004 Presidential
There were 13,660 National Exit Poll respondents and 51.7% said they voted for Kerry. But Bush won the recorded vote by 50.8-48.3%. So the pollsters had to switch 6.7% of Kerry respondents to Bush.

Bush had 50.5 million recorded votes in 2000. Approximately 2 million died and another million did not return in 2004. Therefore, there were at most 47.5 million returning Bush 2000 voters. The National Exit poll indicated that 52.6 million Bush 2000 voters returned in 2004. The pollsters had to create at least 5 million phantom Bush voters. Of course, this made no sense. But who questioned it? Who even knew about it?

2008 Presidential
There were 17,836 National Exit Poll respondents. Obama had 61% in the unadjusted poll but just 53% in the vote count. The adjusted 2008 National Exit Poll indicated that 46% of 2008 voters (60 million) were returning Bush 2004 voters and 37% (48 million) returning Kerry voters.This was impossible; it implied a 103% turnout of living Bush 2004 voters. Bush won the recorded vote by 3 million. But Kerry won the unadjusted exit poll by 6 million and the True vote by nearly 10 million.

2010 Florida Governor
Scott defeated Sink with 50.59% of the 2-party vote. But Sink easily won the unadjusted exit poll by 50.8-45.4% (3150 respondents, 2% margin of error). In order to match the recorded vote, the adjusted exit poll indicated a 47/47% split in returning Obama and McCain voters, 3% were new and 3% returning 3rd party (other) -but vote shares were NA for new and other voters. In order to match the recorded vote, Scott needed 67% of the 6% NA. This is implausible. Based on the unadjusted exit poll, Sink had 57% of this group.

2014 Florida Governor
Scott had 50.58% of the 2-party vote, within .01% of his 2010 share. Just a coincidence? The question How Did You Vote in 2010? was not asked, so let’s look at the Florida exit poll Party-ID demographic. There were 11.9 million registered voters. Democrats outnumbered Republicans by 500,000 (38.8% Dem; 35.0% Rep; 26.2% Other). But in matching the recorded vote, the Party-ID split was 31D-35R-33I. Assuming that the True split was equal to the actual voter registration mix, Crist is the winner by 50.9-44.6%. Crist had stronger support among Democrats (91%) than Scott had among Republicans (88%). He won Independents by 46-44%. So how did he lose?

Florida Gov 2014 Exit Poll (matched recorded vote)
Party-ID.......Mix Crist Scott Wyllie
Democrat........31% 91% 6% 3%
Republican......35% 10% 88% 2%
Independent.....33% 46% 44% 8%
Total...........99% 46.9% 47.2% 4.3%
Votes..........5.88 2.78 2.80 0.25

Florida Gov 2014 Exit Poll (Registration Mix)
Party-ID.......Mix Crist Scott Wyllie
Democrat.......39% 91% 6% 3%
Republican.....35% 10% 88% 2%
Independent....26% 46% 44% 10%
Total..........100% 50.9% 44.6% 4.5%
Votes......... 5.94 3.03 2.65 0.265

2012 Wisconsin Walker Recall
In 2008, Obama won Wisconsin with a 56.2% recorded share. He had 63.3% in the unadjusted exit poll, far beyond the 2.5% margin of error. The exit poll is strong evidence that election fraud sharply reduced Obama’s True Vote.

In 2010, Walker won by 124,638 votes with a 52.3% share. in 2012, he won the recall by 171,105 votes with 53.1%. But the True Vote Model (TVM) showed that he needed 23% of Obama returning voters to match the recorded vote. That is extremely implausible – and a red flag. It’s further evidence that Barrett won the election.

2014 Wisconsin Governor
Walker won with a 52.9% share. In order to match the recorded vote, the adjusted exit poll showed that returning 2012 Barrett voters comprised 35% of 2014 voters compared to 50% for returning Walker voters. The 15% spread is implausible. Compare it to Walker’s 7% recorded 2012 margin and Barrett’s estimated 6% True Vote margin (a whopping 21% discrepancy).Assuming a feasible Barrett 45/Walker 41% returning voter mix, Burke is the winner by 52.3-47.3%.

In the “How Voted in 2012” crosstab, vote shares are missing for Other (3%) and New Voters (DNV 11%). How many of the missing 14% voted for Burke?

An excellent paper from mathematician Kathy Dopp:

Click to access USElections2014.pdf


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Nate Silver and Election Fraud

Richard Charnin
Nov. 17, 2014

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

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

Once again, Nate Silver misdirects his readers in reviewing the 2014 elections. He claims that the polls were biased to the Democrats. He never considers that the polls were close to the true vote but that the vote counts were rigged.

Nate Silver never discusses Election Fraud, even though it has been proven systemic. I pointed this a few years ago in a reply to his post on why we should not believe exit polls. His knowledge of exit polls was (and apparently still is) non-existent.

As usual Nate cites polling “bias”. But not a word about the fact that early pre-election polls include all registered voters (RVs). As we move toward Election Day, the polls are transformed to the subset of Likely Voters (LVs) – with the effect of reducing projected Democratic turnout and vote share.

The true bias is that pollsters skew the projections in order to match the expected fraudulent recorded vote. Nate Silver never considers that the RV polls are usually close to the truth – but that the LV polls are biased against the Democrats. So it’s just the opposite from Nate’s view. He believes the official vote counts are accurate, but researchers who analyze the historical record see a consistent 4-5% “red shift” to the GOP. It is absolute proof that the recorded vote counts are fraudulent and biased for the Republicans.

Nate never discusses the fact that exit polls are always forced to match the bogus recorded vote. The pollsters admit that it is standard operating procedure. Their rationale is that the polls must always be wrong since they deviate so greatly from the recorded vote. Of course we never get to see the unadjusted exit polls until years later, if then. The 1988-2008 unadjusted presidential state and national exit polls showed that the Democrats won by an average of 52-42%. But the recorded vote had them winning by just 48-46%
I just posted the True Vote model for the Wisconsin and Florida governor races. Both races were stolen in 2014- just like they were in 2010 and the 2012 Walker recall. .

In the 2010 Florida Governor election, the unadjusted exit poll and the True Vote Model indicated that Sink won by 5%, yet Scott won the recorded vote by 1%. In 2014, Scott won again. The 2-party vote shares were identical! Scott had 50.59% in 2010 and 50.58% in 2014! A coincidence? Hardly.The Florida 2014 Exit Poll indicates a 31-35-33 Dem-Rep-Ind split (over-weighted for Republicans) with 91% of Dems voting for Crist, 88% of Repubs voting for Scott. Crist won Independents by 46-44%. When we change the split to a more plausible 34-33-33, Crist is the winner by 49.4-45.6%.

In the 2014 Wisconsin Governor election, a True Vote analysis indicates that Walker stole the election, just like the recall in 2012. View the True Vote analysis:

The easiest way to understand that our elections are fraudulent is to look at the 2004 presidential election. According to the adjusted 2004 National Exit Poll (as posted on major media sites), there were 52.6 million returning Bush 2000 voters (43% of the 2004 electorate) and 37% returning Gore voters. Recall that Gore won the popular vote by 540,000. Gore won the unadjusted exit polls by 50-45% (he actually won the True Vote by 3-5 million).

But Bush had only 50.5 million recorded votes in 2000. Approximately 2 million died and one million did not return. Therefore, there were at least 5 million (52.6-47.5) phantom Bush voters. The exit pollsters had to adjust the unadjusted, pristine National Exit poll which showed Kerry a 52-47% winner to make Bush a 51-48% winner. Bush needed an impossible 110% turnout of living Bush 2000 voters to match the recorded vote.

And finally, here is the ultimate proof of systemic election fraud. In the 274 state presidential unadjusted exit polls from 1988-2008, the Democrats won the polls by 52-42%, exactly matching my True Vote Model. But they won the recorded vote by just 48-46%. Of the 274 exit polls 135 exceeded the margin of error, 131 in favor of the Republican. The probability P of that discrepancy is E-116 or
P= 0.0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 000001.

1988-2008 Unadjusted State and National Exit Poll Database

Take anything from Nate Silver with a BIG GRAIN OF SALT. He never mentions PROVEN ELECTION FRAUD . And don’t forget that he had the gall to rank famous pollster Zogby dead last in his evaluation of pollsters a number of years back while ranking dedicated GOP pollsters at the top.

I have written several open-letter posts for Nate. He has not responded to any.

1. An Open Letter to Nate Silver
2. An Open Letter to Nate Silver (Part 2)
3.Twenty-five Questions for Nate Silver
4.A Reply to Nate Silver’s “Ten Reasons Why You Should Ignore Exit Polls”
5. Zogby vs. Silver: 1996-2008 True vs. Recorded Vote Pollster Rankings

The bottom line: Nate works for the major corporate media which is not interested in divulging why pre-election and exit pollsters adjust the polls to match fraudulent vote counts. They will never plead guilty.

This is a summary of my track record in forecasting the 1988-2012 presidential elections, unadjusted exit polls and True Vote Models.

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Posted by on November 17, 2014 in Election Myths, Media, Rebuttals


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Five Wisconsin Elections: A Pattern of County Unit/Ward Vote Share Anomalies

Five Wisconsin Elections: A Pattern of County Unit/Ward Vote Share Anomalies

Richard Charnin
Dec. 23, 2012
Updated: Aug.2, 2015

The purpose of this analysis is to determine if there were repetitive patterns in the cumulative county vote shares in five recent Wisconsin elections. The patterns are obvious; the county graphs are virtual duplicates.

This post is a work-in-process, but since the data tables and graphs are completed, I wanted to make them available while the analysis is ongoing.

The following counties appear most anomalous: Brown, Dane, Jefferson, Kenosha, La Croix, Milwaukee, Oneida, Ozaukee, Racine, Richland, Sheboygan, Trempealeau, Walworth, Washington, Waukesha and Winnebago.

Republican vote shares are increasing (lines slope upward) while Democratic shares decrease (slope downward) at the same rate. This is an indicator of likely vote switching.

Summary of Key Walker Recall Results
Walker won the recall by 171,000 votes (53.1-46.8%).

In 15 large counties, Barrett’s vote shares at 25%, 50% and 100% of the cumulative total were 54.2%, 52.1% and 48.1%, respectively. The counties had 1.51 million of the total 2.52 million recorded votes.

Milwaukee County is the largest and most anomalous. In the recall, Barrett had 63.3% of the total 396,000 votes. But he had 74.4% at the 25% mark, 70.4% at 50% and 66.5% at 75%. Looking at Barrett’s shares in terms of remaining votes, he had 59.4% of the final 75%, 55.9% of the final 50% and 53.0% of the final 25%. In other words there was a 21.4% decline in Barrett’s 74.4% vote share of the first 100,000 votes to 53.0% in the final 100,000 votes.

Barrett’s True Vote Model 54.4% share is within 0.2% of his 15 county cumulative share at the 25% mark. His total Wisconsin share (assuming an equal level of fraud in the other 57 counties) was 52.4%.

In the 15 counties, there was a 6.0% difference between Barrett’s 54.2% at the 25% mark and his final 48.1%. Adding 6.1% to Barrett’s official 46.3% total share, he had an estimated 52.4% Wisconsin True Vote share.

In the 15 counties, there was a 4.0% difference between Barrett’s 52.1% at the 50% mark and his final 48.1%. Adding 4.0% to Barrett’s official 46.3% total share, he had an estimated 50.3% Wisconsin True Vote share.

2008 Presidential Election
The cumulative vote analysis essentially confirmed the unadjusted exit poll. Obama won the WI recorded vote by 56.2-42.7%. He won the unadjusted exit poll 63.3-35.7%, a 7.1% increase over the recorded vote share.

In 15 of the largest counties, Obama’s vote shares at the 25%, 50% and 100% of the cumulative total were 62.4%, 60.6% and 57.1%, respectively. The counties had 1.85 million (62%) of the 2.98 million total recorded votes.

Democratic votes shares declined by an average of 6.0% from the 25% mark to the final recorded vote:

15 Wisconsin Counties
Democratic Vote Share Trend
15 Wisconsin Counties
(Votes in thousands)
.................... Percent of total vote

15 Counties Votes 25% 50% 100% Change
2008 Obama 1853 62.38% 60.59% 57.07% 5.31%
2010 Feingold 1375 54.70% 52.38% 48.69% 6.02%
2010 Barrett 1372 55.04% 51.86% 48.23% 6.81%
2012 Barrett 1551 54.24% 52.11% 48.14% 6.10%
2014 Burke 1511 53.96% 52.22% 48.50% 5.46%

The Spreadsheets
The following spreadsheets use data provided by GAB. Note that Milwaukee County is displayed at the top of the screen in each spreadsheet to illustrate the similar cumulative vote pattern in each of the four elections.

2014 Governor

2012 Walker recall (contains voting machine types for each county and municipality).

2010 Governor

2010 Senate

2008 Presidential

In the process of working on analysis of Wisconsin elections, I have developed a number of models and databases which are available online as Google Doc spreadsheets. They can be linked to from the following posts:


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Walker Recall: County Cumulative Vote Shares by Increasing Unit/Ward Size

Walker Recall: County Cumulative Vote Shares by Increasing Unit/Ward Size

Richard Charnin
Updated: Oct.28, 2013

This is a cumulative vote trend analysis of the Walker Recall by increasing unit/ward vote counts. The data had already been included in The Walker Recall True Vote Database Model. Each county was sorted by size of Unit/Ward. Cumulative vote shares for Walker and Barrett were calculated and the graphs were generated.

The cumulative vote trend graphics is similar to Francois Choquette’s. analysis of the GOP Primaries and Prop.37.

Note the upward sloped lines for Walker in Milwaukee, Racine, Winnebago, Waukesha counties. The Law of Large numbers is violated; we would expect flat or slightly upward sloping lines for Barrett since Democratic shares are usually higher in larger urban wards than in smaller rural ones.

If the lines are flat or upward sloping for Walker, this is an indicator of vote miscount favoring Walker.


Click to access 1410.8868.pdf

The Law of Large Numbers

As the vote count increases, the cumulative vote shares should hardly change (the lines should be nearly flat). But if they diverge, there must be some external factor causing it. It could very well be the FRAUD FACTOR.

Consider this baseball analogy. Why do batting averages fluctuate so greatly in the spring, but less and less as the season progresses? The Law of Large Numbers. Batting average= Total base hits/Total At Bats

Vote share for Walker= Walker Votes/Total Votes (but the Law of Large numbers was violated in the election)

The following counties appear to be the most anomalous: Brown, Milwaukee, Ozaukee, Racine, Richland, Shawano, Sheboygan, Walworth, Waukesha and Winnebago. Why would Barrett’s vote shares in Milwaukee County decline with increasing ward size? Presumably, larger wards are more Democratic than smaller wards. If anything, one would expect the lines to DIVERGE OR AT LEAST REMAIN PARALLEL – NOT CONVERGE.

The Wisconsin True Vote Model indicated that Barrett had 66.0% in Milwaukee compared to his 63.6% recorded share. In Brown, 52.2% vs. 40.0%, Racine 51.5% vs. 46.9%, Sheboygan 47.4% vs. 35.3%; Winnebago 53.5% vs. 43.6%.

Why would Barrett’s Milwaukee County cumulative BLUE vote shares decline while Walker’s RED shares slope upward? It’s a red flag which indicates vote miscounting.

Winnebago County


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The Walker Recall Municipal Database: A True Vote Model

Walker Recall Municipality Database: A True Vote Model

Richard Charnin
Updated: Oct.27,2013

The Recall True Vote Model is designed to be a data reference and forensic tool to uncover locations where fraud was likely. It contains voting data on a county, municipality and ward-by-ward basis.

The analysis shows that the election was very likely stolen. In order to achieve his 171,000 vote margin (53.1-46.3%) Walker’s required shares of returning Obama voters in many municipalities were implausible. The True Vote Model indicates that Barrett had a 53-54% True Vote share (2-party) and won the election by nearly 200,000 votes.

The model produces the following for 72 counties, nearly 1900 municipalities and over 3000 Wards/Units:
1) Recorded votes and True Vote estimates
2) Walker’s share of returning Obama voters required to match the recorded vote
3) Red-shift differential between the True Vote and recorded vote
4) Voter turnout as a percent of living 2008 voters
5) Recorded and True Vote Margin

The ‘Input’ sheet contains the True Vote model for analyzing the state, a county or municipality.

Default Assumptions
Barrett’s share of returning Obama voters is calculated automatically as an incremental partisanship adjustment to his assumed 90% total Wisconsin share.

For example, in Dane County, Barrett’s share of returning Obama voters is adjusted from 90% to 95%. In Waukesha, it is adjusted to 84%.

The default assumption that Barrett won 5% of returning McCain voters is conservative. According to the WI 2010 Exit Poll, Barrett had 7%.

Barrett’s share of voters who did not vote in 2008 is set to Obama’s share.

User can now set their own Barrett shares of returning Obama and McCain voters as defaults on the Input sheet (they were originally hard coded as 90% and 5%). In the 2010 Wisconsin Governor exit poll, Barrett had just 83% of Obama voters. I believe his actual share was better than that. He also had 7% of McCain voters. If Barrett’s share of McCain voters in the recall was 7%, Walker’s required share of returning Obama voters increases from 22% to 24%.

Each of the defaults can be overridden.

Sensitivity Analysis
The tables save the time and effort of asking “what-if” vote share and turnout assumptions change to calculate total vote shares and margins.

Consider these scenarios based on the following assumptions:
1-Equal 79% turnout of Obama and McCain voters
2-New voters are 11% of total 2012 electorate
3-Barrett wins 57% of New voters

Worst Case
Barrett has 87% of returning Obama voters and 4% of McCain voters
He has 52% and wins by 100,000 votes

Most Likely Base Case
Barrett has 90% of returning Obama voters and 7% of McCain voters
He has 54.7% and wins by 232,000 votes

Best Case
Barrett has 93% of returning Obama voters and 10% of McCain voters
He has 57.3% and wins by 366,000 votes

The “Muni” database worksheet is protected from user data entry.
The built-in assumptions:
– Barrett’s default share of Obama voters is 90%, as per the “input” sheet.
– His share of McCain voters is fixed at 7%.
– There is no breakout of new voters.

These are the steps in using the model to analyze a given municipality:
1. Scroll “Muni” to locate the county
2. Check the row number of the Municipality
3. Enter the row number in the ‘Input’ sheet

These articles are from Wisconsin blogger Dennis Kern:

Earlier posts on the Walker Recall:
July 11: True Vote Model: Implausible Walker Vote Shares Required to match the vote.
June 9: Exit Pollsters: MO Never Changes
June 6: Final Exit Poll: Forced to Match the Recorded vote
May 24: Is the Past Prologue?
May 3: True Vote Model Analysis

Take the Election Fraud Quiz.

Winnebago County Cumulative Vote Shares


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Wisconsin Recalls: Exit Polls and the True Vote Model

Sept 7, 2011

In each of the five Citizen Exit Polls conducted in two Wisconsin districts, the Democrats did much better than the official count (67.8% vs. 52.4% on average). Why the large discrepancies? Are the polls to be believed? This analysis provides a possible explanation, keeping in mind that it is based on a limited number of exit poll locations.

The Wisconsin Recall True Vote Model

It is important to understand the difference between the Wisconsin Citizen exit polls and corporate sponsored state and national exit polls in prior elections. The Citizen polls had a very simple aim: to compare how respondents said they voted to the official count.

State and National Exit Polls: Forced to Match the Recorded Vote
Corporate state and national exit polls are designed to determine how various demographic groups voted. The National Exit Pool (NEP) is the consortium of six media giants that funds state and national exit polls.
The NEP uses stratified sampling to select precinct locations that are representative of the voting population.

It is standard operating procedure to force Final state and national exit polls to match the recorded vote. It is also standard policy for the NEP to keep “unadjusted” precinct exit poll data hidden from the public, claiming the need to protect voter “privacy”. It’s a canard; exit poll responders do not reveal their identity. There is no excuse for suppressing the release of unadjusted precinct exit poll data.

Recall Exit Poll Discrepancies
In three strong Democratic recall locations, Democratic exit poll shares (78.8%) were significantly higher than the vote counts (66.9%). Shorewood was 10.9% higher, Pardeeville 8.5% and Baraboo 15.8%. The True Vote Model (TVM) closely matched the recorded votes. Overall voter participation was 52%. If the vote counts were correct, 61% of Democrats and 33% of Republicans responded. Republican voters may have been reluctant to respond in these heavily Democratic locations. If that was the case, then the exit polls overstated the True Democratic vote.

In the two strong Republican locations (Butler and Menomonee Falls), the Democrats had 43.1% in the exit polls compared to 31.5% in the count(16.5% higher in Butler, 11.0% in Menomonee). In the TVM, the Democrats did 11.0% and 8.3% better, respectively. Overall just 33% of voters participated. If the vote counts were correct, then 45% of Democrats and 28% of Republicans responded – an implausible Democratic participation in these strong GOP locations. Therefore, it is likely that the votes were miscounted and the exit polls were close to the True Vote.

The aggregate Democratic True Vote share was 55.2%, a very close match to the 55.5% aggregate share calculated based on equal Democratic and Republican response in each location.

The discrepancies could also have been due to a combination of vote miscounts and differential response. Assuming equal Democratic and Republican response rates, Democratic shares were 73.0% (6.1% higher than recorded) in Democratic locations and 35.4% in Republican locations (3.9% higher).

Republican Exit Poll Response Required to Match Recorded Vote
The total Democratic exit poll response rate was 57%; the Republican rate was 30%. Democratic response exceeded Republican response in each of the five locations. What if the overall Republican response was also 57%? What would the response have to be in each location for the exit poll to match the recorded vote (52.4% Dem, 47.6% Rep)? Using the Excel Solver algorithm, the required Republican response was derived (Democratic response was held constant to the actual exit poll). Republican response was constrained to exceed Democratic response in Menomonee Falls and Butler. The required response rates were not plausible (see the table below). Republican response exceeded Democratic response in 4 of the 5 locations (including Democratic strongholds Pardeeville and Shorewood). In Pardeeville, 100% of Republican voters responded.

Exit Poll Refusal Rates
We define Exit Poll refusals as the difference between the total number of non-responders and the number of non-responders required to match the recorded vote. The refusal rate is the ratio of refusals to the recorded vote. The average Republican refusal rate in Democratic locations was 18.8%: Baraboo 16.6%, Pardeeville 12.9%, Shorewood 22.5%. In Republican locations, the rate was 5.6%: Menomonee Falls 5.9%, Butler 5.2%. Republican voters were four times more likely to refuse an exit poll interview in Democratic than in Republican locations.

Based on the True Vote Model and the exit polls, it is very likely that the District 8 and 14 recall elections were stolen. The Republicans control the state senate by a 17-16 majority, but the Democrats should be in control by 18-15.

True Vote Model
The TVM requires an estimate of the True Vote in the previous election in order to determine a plausible mix of returning voters. In 2008, Obama had a 56.2% recorded vote share in Wisconsin, but he had a whopping 63.3% in the unadjusted exit poll. The margin of error was 2.4% (including a 30% cluster effect) for the 2545 respondents. It is obvious that using a miscounted recorded vote from the previous election as a basis for forecasting or post-election analysis will produce a fraudulent result in the current election.

These were the base case assumptions used in the TVM:
1) Equal percentage turnout of Obama/McCain voters.
2) Zero net defection: Democrats win 95% of returning Obama voters, Republicans win 95% of McCain voters.
3) New voters broke for the Democrats and Republicans in the same proportion as the 2008 recorded vote.

For each exit poll location, a sensitivity analysis table displays Democratic vote shares based on nine scenario combinations of returning Obama and McCain voters. The base case scenario is the central cell of the 3×3 table.

2004 Exit Polls
In 2004, there were 1480 exit poll precinct polling locations nationwide. More than 76,000 voters participated. To explain the average 6.5% exit poll discrepancy, the exit pollsters hypothesized that 56 Kerry voters participated for every 50 Bush voters. They provided no evidence for this. They did not consider that the discrepancies may have been due to Election Fraud. The so-called reluctant Bush responder (rBr) theory was refuted by the exit pollster’s own data which showed that exit poll response was higher in Bush strongholds than Kerry strongholds.

Link to the source data tables:


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Nine Wisconsin Recalls: A True Vote Analysis

A Statistical Analysis of the Wisconsin Recall Elections

Richard Charnin

Aug. 17, 2011

The numerical analysis is based on the Wisconsin Recall True Vote Model.

The Democrats won 5 of the 9 recall elections and won the overall popular vote with a 50.5% share. In 2008, Obama won all 9 districts with a 54.5% share.

The Republicans won 4 of the 6 GOP districts with 55.2%. Obama had 51.5% in the four districts. To accomplish this, there had to be an implausibly low Obama voter turnout and/or an implausibly high defection of Obama voters.

The Democrats did 3.2% better than Obama in the three Democratic recalls, but 5.4% worse in the 6 GOP recalls, an implausible difference.

In the GOP districts, voter turnout was 65% of the 2008 presidential election; it was 48% in Democratic districts.

These anomalies, combined with documented evidence of voting irregularities and exit poll results, are very strong indicators of Election Fraud. It is very likely that the Democrats won at least seven of the nine elections.

In the 6 GOP recall elections, 65% of Obama and McCain voters returned to vote. Assuming zero net defection, approximately 58% of Obama voters and 85% of McCain voters turned out. That is a very implausible difference. Assuming equal 65% turnout, the Democrats won 82% of Obama voters and Republicans won 92% of McCain voters – an implausible 10% net Obama defection.

In the 2 GOP districts won by the Democrats with an average 53.2% share, Obama had 55.9%. Total turnout was 66%. Approximately 63% of Obama voters turned out. That is plausible. Assuming equal turnout, the Democrats won 91% of Obama voters and 5% of McCain voters. Very plausible.

The 3 Democratic recall elections were landslides. The Democrats had a 58.8% aggregate share. Obama had 55.5%. Approximately 48% of 2008 voters turned out. Assuming zero net defection, 52% were Obama and 44% McCain. That is plausible. Assuming equal 48% turnout, the Democrats won 98% of Obama and 8% of McCain voters (6% net McCain defection). Also plausible.


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Can the GOP win the Aug 16 Democratic Recall Elections?

Can the GOP win the Aug 16 Democratic Recall Elections?

Richard Charnin

August 16, 2011

Election results are always a function of voter turnout, returning voter preference and…election fraud.
This is a scenario analysis to determine what it would take for the Democrats to lose one or both seats.

In the base case scenario we assume equal turnout of Obama and McCain voters, zero net defection and no fraud.
The sensitivity analysis tables display Democratic vote shares over a range of turnout and voter preferences.

District 12 is vulnerable.

In 2008, Obama had 52.5% in District 2 – and the GOP won the recall.
Obama had 52.8% in District 12.

Pre-election polls show Holperin winning,
Holperin will win, assuming zero fraud, zero net defection and equal turnout rates of Obama and McCain voters.

But he could still lose – if the election is stolen.
Assuming equal turnout rates of Obama and McCain voters, the GOP needs a 6% net defection of returning Obama voters to win.
Assuming equal turnout and zero net defection, the GOP would have to switch 4% of Holperin’s votes.

District 22 appears safe. Obama had 57.3% in the district.

Assuming equal turnout, the GOP needs a net 13% defection of Obama voters to capture the seat.
Assuming equal turnout and zero defection the GOP needs to switch 9% of Wirch’s votes.

Link to the source data analysis tables:


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Will the Democratic Recall Elections be Stolen? A True Vote Analysis

Will the Democratic Recall Elections be Stolen? A True Vote Analysis

Aug. 13, 2011

Richard Charnin

The Democrats won two of the six GOP recall elections. A post-election True Vote analysis indicates that they may have won all six.

The Republicans now have a 17-16 majority in the senate. But it won’t be enough to enact Walker’s agenda if just one Republican defects and votes with the Democrats. Now the Democrats need to defend two seats in the final recall elections: Jim Holperin in District 12 and Bill Wirch in District 22. The GOP needs one to get an 18-15 foolproof majority. Let’s see what it would take for the GOP to win a seat.

The analysis is based on the Wisconsin Recall True Vote Model.

In any election, there are two key factors: voter turnout and voter preference. We know how many voters returned from the previous election (as a percentage). But we must estimate the percentage mix of returning Democrats and Republicans. The number of new voters is just the difference between total votes cast in the current election and returning voters. In the recall analysis, we will assume that new voters were split equally between the Democrats and the Republicans.

District 12:
Obama had 52.8%. Election fraud could cost the Democrats this seat (the GOP “won” District 2 where Obama had 52.5%).

Case 1: Zero net defection.
Democrat Holperin wins 95% of returning Obama voters and 5% of returning McCain voters.
The GOP wins if 60% of McCain voters turn out and fewer than 52% of Obama voters do.

Case 2: Assume equal 60% Obama and McCain turnout
The GOP wins if Holperin captures fewer than 88% of Obama voters.

District 22:
Obama had 57.3%. The probability that the Democrats will hold the seat is virtually 100%.

Case 1: Zero net defection.
Democrat Wirch wins 95% of returning Obama voters and 5% of returning McCain voters.
The GOP wins if 60% of McCain voters turn out and fewer than 45% of Obama voters do.

Case 2: Equal 60% Obama and McCain turnout
The GOP wins if Wirch captures fewer than 83% of Obama voters.

Click for the numerical sensitivity analysis tables.


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Wisconsin Recall Election Projections

Wisconsin Recall Election Projections

Aug. 4, 2011

Richard Charnin

The Democrats need to win 3 of 6 GOP seats in the recall elections to gain control of the Wisconsin senate.

Assuming the Wisconsin 2008 presidential election
1) Recorded vote shares and fraud in the recalls, the Democrats will likely win 1 or 2 GOP seats.
2) Recorded vote shares and zero fraud in the recalls, the Democrats will likely win 3 GOP seats.
3) True Vote shares and zero fraud in the recalls, the Democrats will likely win all 6 GOP seats.

The Wisconsin Recall Projection Model is based on the following assumptions for each of the 6 GOP districts:
1. 2008 Presidential Election recorded vote
2. Estimated 2008 Fraud Factor (i.e. reduction in Obama’s True District vote share)
3. Obama voter turnout rate in recall
4. McCain voter turnout rate in recall
5. Democratic share of returning Obama voters
6. Democratic share of returning McCain voters

For the selected district, two sensitivity analysis tables display nine Democratic vote share scenarios based on
1) Democratic vote shares of returning Obama and McCain voters
2) Obama and McCain turnout rates

Base Case Assumptions
1) Equal 63% Turnout of Obama and McCain voters
2) Democratic 91% share of Obama voters
3) Democratic 5% share of McCain voters

Recall Election Fraud Scenarios
Assume that…
1) Obama’s Wisconsin True Vote was 1% higher than recorded
2) Equal Obama/McCain percentage turnout in the recall elections
3) Democrats win 92% of Obama voters and 5% of McCain voters
The GOP needs to flip 2% of Democratic votes to retain senate control. Assuming the Democrats win 94% of returning Obama voters, the GOP would need to flip 3%.


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