RSS

Monthly Archives: September 2012

A Compendium of Election Fraud Links

A Compendium of Election Fraud Links

Wisconsin Recalls True Vote Models
True Vote Model/ Election Fraud Graphics
Unadjusted exit polls
RV Polls vs. LV Polls: Likely Voter Cutoff Model
Exit Poll Red shift probabilities
True Vote Model Analysis
Monte Carlo Electoral Vote Forecast Simulation
Election Fraud Models
Forcing the Exit Poll to Match the Recorded vote
1988-2008 Stolen Elections
1988-2008 Exit Poll Red-shift Probabilities
True Vote Sensitivity Analysis
Election Forecast Sensitivity Analysis
2000 Florida NORC Recount
Voter Fraud vs. Election Fraud
Exit Poll Myths: Reluctant Bush Responder, False Recall and Swing vs. Redshift

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 (2-party shares)
Obama 51.6%, 332 EV (Snapshot)
Recorded : 51.6%, 332 EV
True Vote 55.2%, 380 EV

 
Leave a comment

Posted by on September 27, 2012 in Uncategorized

 

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

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

Richard Charnin
Sept. 26, 2012

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

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

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

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

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

2004 and 2008 Election Models

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

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

Forecast Summary

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

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

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


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

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

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

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

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

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

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

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

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

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

The True Vote Model

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

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

Sensitivity analysis

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

Monte Carlo Simulation: 500 election trials

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

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

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

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

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

Electoral Votes and Win Probabilities

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

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

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

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

The Fraud Factor

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

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

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

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

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

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

Election Model Projections: 2004-2010

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

2004 Election Model Graphs

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

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

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

2008 Election Model Graphs

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

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

Pre-election RV and LV Polls

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

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

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

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

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

Election Model Forecast; Post-election True Vote Model

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

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

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

 
Leave a comment

Posted by on September 26, 2012 in 2012 Election

 

Tags: , , , , , , , , , , ,

The Walker recall: A correlation analysis of voting machines

The Walker recall: A correlation analysis of voting machines

Richard Charnin
Sept. 25, 2012

The purpose of this Walker recall voting machine analysis is to determine the effect of paper ballots, touch screens (DRE) and optical scanners on county and municipal vote shares.

Note that this analysis is not as complete as it should be. There is no breakdown of votes in locations where there were several types of voting machines. Only the voting machine percentages are available. The analysis will be updated when and if votes in each location by machine type are released.

We need the data in the same form as used in this analysis of Winnnebago County vote counts in which probabilities of vote share differentials in the same unit/ward were calculated. Theoretically differences in the shares should have been minimal, say within 5%. But there were much larger discrepancies in a number of locations.

Using the municipal voting machine mix, there was a negative (-.24) correlation between Barrett’s county vote shares and corresponding percentage of total votes cast on DREs. Overall Barrett did better on paper ballots (.11) and optical scanners(.14). As the percentage of votes cast on DREs increased, so did Walker’s share.

The source of the data is the Wisconsin Government Accounting Board Form 190- Voting by Type of Equipment. I created this spreadsheet for the correlation analysis.

Of the 59 counties Walker won, 54 used touchscreens (DREs). But the majority of votes were cast on optical scanners.

In the 13 counties Barrett won, just five had DREs. These were the percentages of DRE votes: Iowa (76%), Eau Claire (21%), Kenosha (12%), Columbia (0.2%) and Milwaukee (0.5%). The total number of DREs was negligible in the counties.

Several correlations were calculated. The first set was to determine if there was a relationship between the municipal vote shares and the percentage of DRE votes cast in each municipality.

The correlation between votes cast on optical scanners and county vote size was 0.45. The larger counties used optical scanners almost exclusively. The correlations were -0.41 for DREs and -0.31 for paper ballots. DREs and paper ballots were mostly used in smaller counties.

In addition, correlation ratios measured the strength of the relationship between voting machines and county vote shares. Voters were encouraged to use DRE’s rather than paper ballots.

In the counties Walker won, Barrett’s vote shares were positively correlated to the percentage of paper ballots (.20) and to votes cast on DREs (0.17). His shares were negatively correlated to optical scanners (-0.21).

In the top ten Walker counties (highest vote shares), 85% of votes were cast on optical scanners, 10.7% on DREs. In the top ten Barrett counties, 96% of votes were cast on optical scanners, 1.2% on DREs.

In counties won by Walker, 76% of votes were cast on scanners, 18% on DREs.
In counties won by Barrett, 95% of votes were cast on scanners, 2.7% on DREs.

Winnebago County- Cumulative Vote Shares

 

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

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

Richard Charnin
Sept. 26, 2012
Updated: Nov.5, 2012

This is the final Nov.5 projection: 2012 Presidential True Vote and Monte Carlo Simulation Forecast Model.

It was exactly right: Obama had 51.6% (2-party) and 332 EV with a 99.6% win probability. But his True Vote was 55% with 380 EV.

The 2008 Election Model also predicted Obama’s recorded vote exactly: 365 EV, 52.9% and 100% win probability. But his True Vote was 58.0% with 420 EV.

Forecast Summary

Obama has extended his expected Electoral Vote by gaining the lead in the latest North Carolina and Iowa polls. He has a 49-44% lead in the latest state polls with 342 expected electoral votes based on the state win probabilities.

Obama leads the Real Clear Politics National Average by 48.9-44.9% and has extended his lead in the Gallup tracking poll to 50-44%.

If the election were held today, the Monte Carlo electoral vote simulation indicates that he would have a 100% probability of winning the election (he won all 500 election simulation trials). But there are six weeks to so. Will there be an October surprise?

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

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

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

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


9/19/2012
True Vote Model Obama Romney
True Vote...... 56.3% 43.7%
Expected EV.... 402 136 (theoretical based on state win probabilities)
Snapshot EV.... 410 128 (simple sum based on state projections)
EV Win Prob.... 100% 0%

State Polls
Average........ 49.2% 44.3% (weighted average of latest polls)
Projection..... 52.4% 47.6% (assume equal split in undecided voters)
Win Probability 94.5% 5.5% (Popular vote, 3.0% MoE)
Expected EV.... 342.4 195.6 (simulation mean value)
Snapshot EV.... 343 195 (sum of projected state votes)

National Polls
Average........ 48.9% 44.9% (RCP latest polls)
Projection..... 52.0% 48.0% (equal 50% split in undecided voters)
Win Probability 97.5% 2.5% (Popular vote, 2.0% MoE)
Gallup......... 50% 44% Registered voter tracking poll (3050, 2% MoE)
Rasmussen...... 46% 46% Likely voter tracking poll (1500, 3% MoE)

Simulation
Projection..... 52.4% 47.6%
Mean EV........ 341.8 196.2 (500 trial elections)
Maximum EV..... 375 163
Minimum EV..... 309 229
Win Probability 100% 0% (Electoral Vote, 500 wins in 500 election trials)

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

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

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

The 2008 True Vote Model (TVM) determined that Obama won in a landslide by 58-40.3%. Based on the historical red-shift, he needs at least a 55% True Vote share to overcome the systemic 5% fraud factor. The TVM was confirmed by the unadjusted state exit poll aggregate: Obama had an identical 58-40.5% margin (76,000 respondents). He won unadjusted National Exit Poll (17,836 respondents) by an even bigger 61-37% margin.

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

The True Vote Model

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

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

Sensitivity analysis

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

Monte Carlo Simulation: 500 election trials

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

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

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

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

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

Electoral Votes and Win Probabilities

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

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

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

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

The Fraud Factor

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

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

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

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

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

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

Election Model Projections: 2004-2010

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

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

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

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

Pre-election RV and LV Polls

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

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

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

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

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

 
5 Comments

Posted by on September 20, 2012 in 2012 Election, Uncategorized

 
 
Follow

Get every new post delivered to your Inbox.

Join 771 other followers