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JFK Assassination: Researchers discuss John McAdams

JFK Assassination: Researchers discuss John McAdams

Richard Charnin
April 6, 2014

A series of articles (including three of mine) on John McAdams, the relentless Warren Commission apologist. http://richardcharnin.com/JMLaughingStock.html

The articles thoroughly debunk the pathetic arguments from the Professor of Disinformation. I enjoyed the devastating reviews of McAdams’ book “JFK Assassination Logic” by Pat Speer, David Mantik, Frank Cassano and Gary Aguilar.

Jim Hargrove asks: Since Mcadams is known to use the alias “Paul Nolan” just how many other names has he used to deceive? He claims to be many things. A jet-propulsion expert, or Crackpot?
Here is what was discovered.

Isabel Kirk: McAdams is not just a fraud as a teacher. He is a corrupt man. He is an evangelist for corruption and fraud. He has sought and enlisted disciples, and they employ his knowingly fraudulent “methodology” in their writing “assignments,” many of which are posted to the website of Marquette University.

Jim DiEugenio with Brian Hunt:
“McAdams did indeed make comments that were intended to imply that Gary Aguilar was a drug addict. IMO, they were deliberate, malicious and intended to smear the doctor.”

John Simkin: “The Education Forum”
If you do any research of major figures in the JFK assassination via web search engines you will soon find yourself on John McAdams’ website. He is clearly the main disinformation source on the net.

Debra Hartman writes:
…McAdams has neither the educational preparation nor the ability for such a position — his language skills are abysmal; his analytical skills non-existent. Not only has he done no research whatsoever on the historical question he pretends to study, he has no knowledge of even the basics of a research methodology. Thus, McAdams himself argues against long established historical facts; on the other hand, he is incapable of doing the research necessary to either confirm or dispute such facts.

And on and on….

I just added an Amazon book sales sheet to JFK Calc.
Judyth Baker’s “Me and Lee” has the highest reader rank at 4.70.

McAdams’ book is far down the totem pole with a 2.38 reader rating out of 5. His sales rank is at 944,700, far below the others. He is a laughingstock all right.

The average rank for the six books that are fact-based is 4.51. McAdams’ 2.38 rank is based on disinformation.

McAdams has had just 16 reviews in three years. NINE (9) are at level 1 (the lowest), 1 is at level 2. Only 3 are level 5. Ten of 16 reviews thought his book stunk. Compare that to Judyth Baker who had 188 reviews in three years with 163 at level 5.

Of the 6 factual books, 793 of 1039 reviews (76%) were at level 5. For McAdams, 3 of 18 (19%) were at level 5.

IT’S NO CONTEST: JFK RESEARCHERS HAVE WON THE DEBATE HANDS DOWN. ONLY MAINSTREAM MEDIA AND WARREN COMMISSION APOLOGISTS LIKE MCADAMS WON’T ADMIT IT.

https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDFSU3NVd29xWWNyekd2X1ZJYllKTnc#gid=75

Amazon Reader ranks (1 lowest to 5 highest)
Published -Title-Author
Sales rank 1 2 3 4 5 Total Average

4/2013 Hit List: Belzer, Wayne
33985 10 1 10 29 74 124 4.26

10/2013 Survivors Guilt: Vince Palamara
88519 8 3 2 7 83 103 4.50

10/2013 They Killed Our President: Ventura, Russell, Wayne
26202 12 2 11 36 125 186 4.40

10/2010 JFK and the Unspeakable: James Douglass
7441 23 11 16 37 333 420 4.54

10/2013 Crossfire: Jim Marrs
47599 1 0 0 2 15 18 4.67

10/2011 Me and Lee Judyth Baker
53426 7 2 6 10 163 188 4.70 < THE BEST

9/2011 How to Think About Claims of Conspiracy: McAdams
944700 9 1 0 3 3 16 2.38 < THE WORST

 
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Posted by on April 6, 2014 in JFK, Uncategorized

 

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Spreadsheet Links: JFK Witness Probability Database, True Vote Models, Unadjusted Exit Polls

Spreadsheet Links

Richard Charnin
Nov.1, 2013

http://richardcharnin.com/

JFK Calc: http://richardcharnin.wordpress.com/2013/10/14/jfk-witness-deaths-graphical-proof-of-a-conspiracy/ http://richardcharnin.wordpress.com/2014/04/09/jfk-calc-questions-on-the-spreadsheet-analysis/ 

https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDFSU3NVd29xWWNyekd2X1ZJYllKTnc#gid=1

1988-2008 Unadjusted Exit Polls: http://richardcharnin.wordpress.com/2011/11/13/1988-2008-unadjusted-state-exit-polls-statistical-reference/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdFIzSTJtMTJZekNBWUdtbWp3bHlpWGc#gid=15

1988-2012 State and National True Vote Model: http://richardcharnin.wordpress.com/2011/09/16/footprints-of-systemic-election-fraud-1988-2004-state-exit-poll-discrepancies/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGN3WEZNTUFaR0tfOHVXTzA1VGRsdHc#gid=0

1968-2012 National True Vote Model: http://richardcharnin.wordpress.com/2013/01/24/1968-2012-presidential-election-fraud-an-interactive-true-vote-model-proof/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdFpDLXZmWUFFLUFQSTVjWXM2ZGtsV0E#gid=4

2012 True Vote Model:http://richardcharnin.wordpress.com/2012/10/17/update-daily-presidential-true-voteelection-fraud-forecast-model/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDQzLWJTdlppakNRNDlMakhhMGdGa0E#gid=14

2004 Election Monte Carlo Forecast and Exit Poll Simulation: http://richardcharnin.wordpress.com/2011/09/01/monte-carlo-simulation-election-forecasting-and-exit-poll-modeling/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDU5VERHay1mZExaT0lMRVhOXzg2aHc#gid=1

2004 County Presidential True Vote:http://richardcharnin.wordpress.com/2012/03/06/2000-2004-presidential-elections-county-true-vote-model/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDNzZWhMcF9sS3pHRWdUZE8zdEs4aGc&usp=drive_web#gid=23

Walker Recall: https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDRwcWRPTUZoZk53YUlxOEVMT0FnX3c#gid=36

Walker Recall: County/Muni True Vote:http://richardcharnin.wordpress.com/2012/07/24/the-walker-recall-municipal-database-a-true-vote-model/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdEd0NFV5QV9DclZFTDJ3aHpqRVh4LWc&usp=drive_web#gid=1

Walker Recall Cumulative Vote Shares: http://richardcharnin.wordpress.com/2012/12/09/walker-recall-county-cumulative-vote-trend-by-ward-group/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdF95dGdleVBSYkdISmplWVZXdXlQQ0E&usp=drive_web#gid=1

Wisconsin True Vote: Supreme Court, State Senate Recalls, 2010 Senate: http://richardcharnin.wordpress.com/2011/08/11/did-the-gop-steal-the-wisconsin-recall-elections-a-true-vote-analysis/ https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdDVmLVZzZVhsVUhRUTFaanFaZG82cFE#gid=2

2008 WI Presidential Cumulative Vote Shares: https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdHRSak5RNHNWUTdWYjNLYlFNUzlxLXc#gid=1

Latin American Leader Cancer: https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdGFXXzNqT1NYdjNVMWpBc0dDaEN0R0E&usp=drive_web#gid=0

 
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Posted by on November 1, 2013 in Uncategorized

 

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Exposing the Media and Coincidence Theorists (CTs) in the JFK Cover-up: Facts, Logic, Mathematics

Richard Charnin:

Important updated information.

Originally posted on Richard Charnin's Blog:

Exposing the Media and Coincidence Theorists (CTs) in the JFK Cover-up: Facts, Logic, Mathematics

Richard Charnin
June 24, 2013
Updated: Sept. 24, 2013

JFK Blog Posts
JFK Calc Spreadsheet Database

There are actually two JFK conspiracies. The first was the assassination itself. The second is ongoing: the corporate media and academia persist in their relentless cover-up of the facts. But Warren Commission apologists and Lone Nutter claims are easily debunked – and make the corporate shills who appear on cable every night look ridiculous.

Suppose that on Nov. 22, 1963, 1400 individuals were selected from the entire U.S. population. Further suppose that within one year, at least 18 would die unnaturally (homicide, accident, suicide) under mysterious circumstances. Based on unnatural mortality rates, only one such death would be expected.

There are two possibilities. The 18 unnatural deaths were…
1) unrelated. It was just a 1 in 1000 trillioncoincidence.

View original 637 more words

 
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Posted by on June 27, 2013 in Uncategorized

 

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Latin American Leaders and Cancer: A Probability Analysis

Latin American Leaders and Cancer: A Probability Analysis

Richard Charnin

Mar. 14, 2013

Hugo Chavez was one of seven (six leftist) Latin-American leaders recently diagnosed with cancer. Columbia’s conservative President Juan Manuel Santos was struck with prostate cancer after beginning peace talks with left wing FARC. The six leftists: Brazilian President Dilma Rousseff, Paraguay’s Fernando Lugo, former Brazilian leader Luiz Inácio Lula da Silva, Argentina’s former President Nestor Kirchner. Argentina’s current President Cristina Fernández de Kirchner was diagnosed with thyroid cancer in December 2012, although later analysis proved she had never actually suffered from the illness. In 2006, it was reported that retired Cuban leader Fidel Castro was also diagnosed with cancer, so there were at least EIGHT in total.

To estimate the probability that a given number of n individuals in a group of size N would be diagnosed with cancer, the following information is required:
1) Average age of the group and associated 10 year cancer rate
2) Size of the group (N)
3) Number (n) diagnosed with cancer

The calculations are estimates based on the BINOMIAL DISTRIBUTION.
P (at least n) = 1- binomdist (n-1, N, rate, 1)

The following spreadsheet contains two probability tables:
1 – For a Given Average Age: Group size vs. number diagnosed with cancer
2 – For a Given Group Size: Average age vs. number diagnosed with cancer

For the following probabilities, the assumed average age of Latin American leaders is 60 (10.13% cancer rate).
Note that Castro was diagnosed in 2006.

-The probability is 0.26% (1 in 389) that at least SEVEN of ALL 20 Latin American leaders would be diagnosed with cancer. Including Castro, the probability is 0.05% (1 in 2203) that 8 would be diagnosed.

-Assuming 10 leftist leaders, the probability that AT LEAST 5 would be diagnosed with cancer is approximately 0.17% (1 in 577). The probability that AT LEAST 6 would be diagnosed is approximately 0.02% (1 in 6330).

-Assuming 14 leftist leaders, the probability that AT LEAST 5 would be diagnosed with cancer is approximately 0.97% (1 in 103). The probability that AT LEAST 6 would be diagnosed is approximately 0.16% (1 in 634).

-Assuming 18 leftist leaders, the probability that AT LEAST 5 would be diagnosed with cancer is approximately 2.96% (1 in 34). The probability that AT LEAST 6 would be diagnosed is approximately 0.68% (1 in 146).

Data Source: National Cancer Institute (SEER)

 
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Posted by on March 14, 2013 in Uncategorized

 

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A Model for Estimating Presidential Election Day Fraud

A Model for Estimating Presidential Election Day Fraud

Richard Charnin
Jan. 1, 2013

Given 1) early voting (mail-in or hand-delivered paper ballots) and 2) late vote (absentees, provisional ballots) and 3) the total recorded vote, what is the Election Day vote share required to match the recorded vote?

This 2012 election fraud analysis shows that Obama’s Election Day vote share was 3% lower than his total recorded share (a 6% discrepancy in margin). It is a strong indicator that votes were stolen on Election Day. Obama’s late vote share was 10% higher than his Election Day share.

In 2012, there were 11.677 million late recorded votes (9.0% of the total). The late vote for each state is the difference between the current and Election Day votes. Obama had 60.2% of the two-party late vote and 51.96% of the total two-party vote.

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’s weighted aggregate state late vote was 57-39%, just 1% lower than the weighted exit polls and the True Vote. In 2012, it was 54-42%, closely matching the 56% two-party True Vote model share.

In 2008, approximately 30% of total votes were cast early. Early vote rates for each state were set to the 2008 rate. Early vote shares were based on information supplied to the media. If the early vote estimate was not available, the assumption is that Obama did 2-3% lower in early voting than late.

Obama’s True Vote margin is estimated to be 15.7 million (56.1-43.9%).

Total Votes Recorded = Early Vote + Election Day Vote + Late Vote

In order to determine the Election Day vote, a simple trial and error (goal-seeking) procedure was used by adjusting the Election Day share until the total share matched the recorded vote. This is analogous to the exit pollsters stated procedure of adjusting the exit poll to match the recorded vote in each demographic cross tab by changing weights and/or vote shares. The National Exit Poll forced a match to the recorded vote in a number of elections by adjusting actual exit poll results using mathematically impossible weightings (millions more returning voters from the previous election than were alive to vote in the current election).

In this analysis, we use actual early and late recorded vote data to determine the Election Day 2-party share required to match the total recorded vote. Unlike the media, the “goal-seek” is to determine the fraud component, not ignore it.

On Election Day, Votes cast on optical scanners and DREs are vulnerable to miscounts on the central tabulators.

Florida
Percent of total vote: Early 52%; Late 2%
To match his 2-party share (49.3%), Romney needed 51% on Election Day.

Ohio
Percent of total vote: Early 25%; Late 4%
To match his 2-party share (48.4%), Romney needed 51% on Election Day.

Iowa
Percent of total vote: Early 36%; Late 2%
To match his 2-party share (51.1%), Romney needed 70% on Election Day.

North Carolina (zero late vote?)
Percent of total vote: Early 60%; Late 0%
To match his 2-party share (47.3%), Romney needed 51% on Election Day.

California
Percent of total vote: Early 45%; Late 27%
To match his 2-party share (38.1%), Romney needed 46% on Election Day.

Arizona
Percent of total vote: Early 53%; Late 29%
To match his 2-party share (54.9%), Romney needed 60% on Election Day.

Virginia
Percent of total vote: Early 14%; Late 4%
To match his 2-party share (48.0%), Romney needed 51% on Election Day.

New Mexico
Percent of total vote: Early 62%; Late 2%
To match his 2-party share (45.1%), Romney needed 48% on Election Day.

Georgia
Percent of total vote: Early 53%; Late 1%
To match his 2-party share (53.1%), Romney needed 58% on Election Day.

National Vote – forced to match the recorded share
How Voted (2-party)………….Votes Pct Obama Romney
Early voting (paper)…………40.6 32.0% 55.0% 45.0%
Election Day…………………75.0 59.1% 49.0% 51.0%
Late Votes (paper)…………..11.2 8.9% 60.2% 39.8%

Recorded Share……….126.8 100.0% 51.9% 48.1%
Total Votes (mil)………………………… 65.85 60.98

…….. Obama Election Day %
…….. 49.0% 52.0% 56.0%
Early Obama Share
56.0% 52.2% 54.0% 56.4%
55.0% 51.9% 53.7% 56.1%
49.0% 50.0% 51.8% 54.1%
Margin
56.0% 5.7 10.2 16.2
55.0% 4.9 9.4 15.4
49.0% 0.0 4.5 10.5

 
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Posted by on December 7, 2012 in 2012 Election, Uncategorized

 

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

Election Fraud: Uncertainty, Logic and Probability

Oct. 29, 2012

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

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

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

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

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

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

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

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

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

Election Model Forecast; Post-election True Vote Model

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

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

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

 
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Posted by on October 29, 2012 in Uncategorized

 

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Calculating the Projected Electoral Vote

Calculating the Projected Electoral Vote

Oct. 26, 2012

The 2012 Election Forecast Simulation Model calculates the projected electoral vote in three ways.

1. Snapshot EV: The state electoral vote goes to the projected leader based on the pre-election poll. This is a crude estimate in close races in which the projected margin is within 1-3%.

2. Expected EV: The probability of winning each state is calculated using the poll-based projection. The theoretical forecast electoral vote is the weighted sum of the state win probabilities and corresponding electoral votes. EV= ∑ P(i) * EV (i), i =1,51 states. This is the best estimate for the projected Electoral Vote.

3. Simulation Mean EV: The mean electoral vote is a simple average of the simulated trial elections. It calculated mean approaches the theoretical expected EV as the number of trials increase (500 is sufficient), illustrating the Law of Large Numbers. A Monte Carlo simulation is needed to calculate the probability of winning the election. It is simply the number of winning trials divided by 500.

The Final Nov.6 model forecast that Obama would have a 332 Snapshot EV (exactly matching his actual EV), a 320.7 Expected EV and 320.8 Simulation Mean EV. But the Expected EV is a superior forecast tool since it eliminates the need for stating that “the states are too close to call”.

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

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

 
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Posted by on October 27, 2012 in 2012 Election, Uncategorized

 

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The Gallup Battleground Poll: an 8% Discrepancy from the state polls

The Gallup Battleground Poll: an 8% Discrepancy from the State polls

Richard Charnin
Oct. 16, 2012

The corporate media has been very busy today claiming that the Gallup poll shows Romney winning the battleground states by 4%. But according to the latest state polls, it’s exactly the opposite.

The latest state polls are in the 2012 Presidential True Vote/ Election Fraud Forecast Model.

Obama leads by 49.3-46.3% in 13 (131 EV) of 17 (198 EV) Battleground state polls weighted by state voting population.

View the numbers in this sheet (scroll down to row 119).

The Monte Carlo simulation gives Obama a 98.2% win probability if the election were held today. He has 306 expected electoral votes.

 
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Posted by on October 16, 2012 in Uncategorized

 

Early Voting: good for Obama. Election Day Voting: not so much

Early Voting: good for Obama. Election Day Voting: not so much

Richard Charnin
Oct. 15, 2012

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

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

Early voting appears to be strongly for Obama – just like in 2008. This analysis compares early voting by mail or hand-delivered paper ballots to Election Day voting.

The objective is to estimate 2008 Election Day vote shares for each state given its early voting percentage, unadjusted exit poll and recorded vote share.

In 2008, 40.6 million (30.6%) of 131.3 million votes were cast early on paper ballots that were hand-delivered or mailed in. Mail-in ballots accounted for 31.7% of early votes.

Analysis of 2008 exit poll data shows that the states which voted early had the highest percentage of early votes had the lowest exit poll discrepancies (red-shift).

Obama had 58.0% in the state exit poll aggregate, but just 52.9% recorded. The assumption in this analysis is that early vote shares were approximately equal to the unadjusted exit polls – and Obama’s True Vote.

Election Day vote shares required to match the recorded vote are calculated using this formula:

Election Day share = (Recorded share – Early vote share) / Election Day share of total vote

Therefore, Obama’s estimated Election Day share was approximately:
50.5% = (52.9 – 58.0*.31) / .69 = (52.9-17.8) / .69

Note: Obama’s total early vote was equal to his 58% exit poll times the early voting share of the total recorded vote. Therefore, assuming Obama had 58% of the 31% who voted early, he must have had a 50.5% share on Election Day. The 7.5% discrepancy from his True 58% share was likely due to the systemic election fraud factor.

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

 
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Posted by on October 15, 2012 in 2012 Election, Uncategorized

 

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True Vote Model Scenarios: What will it take for Romney to win?

True Vote Model Scenarios: What will it take for Romney to win?

Richard Charnin
Oct. 6, 2012

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

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 True Vote Election Simulation Model consists of two components: a Monte Carlo Simulation, based on the latest state polls; and the True Vote Model, based on 2008 voter turnout in 2012 and corresponding vote shares of returning and new voters.

The state polls will be updated on Monday, Oct. 8. In the meantime, let’s consider an analysis that never appears in the mainstream media or by pollsters and election forecasting bloggers.

Obama is leading in the polls, but the race is “tightening”. Yes, once again, we have another media-induced “horse race”. This analysis does not consider pre-election polls. It is concerned with returning voter turnout and defection scenarios and uses the True Vote Model component.

The model shows that in order for Romney to win, he needs a 5% net turnout percentage advantage of returning McCain voters as compared to Obama voters. And he needs to capture nearly one out of five returning Obama voters (18% defection rate) while Obama wins just one in twenty (5% defection rate) returning McCain voters.

Obama won the 2008 state unadjusted exit poll aggregate by 58-40%. The True Vote Model indicated that he had the identical 58%. He won the National Exit Poll by a 61-37% margin. The 8% discrepancy is eight times the theoretical 1% margin of error. The probability of election fraud was 100% in 2008.

Given the above we will assume the following:
1.Obama had 58% in 2008, not the recorded 53%.
2.New voters will split 50/50 for Obama and Romney.

Note that the 50/50 split in new voters is a conservative assumption. According to the adjusted 2008 Final National Exit Poll, which understated Obama’s unadjusted share by 8% in matching the recorded vote, Obama had 72% of new voters. The Democrats have consistently won a solid majority of new voters in every election since 1988.

Let’s now calculate several alternative scenarios to see what it would take for Romney to win, given the above assumptions.

Scenario I: Equal returning Obama and McCain 95% voter turnout and zero net defection of Obama and McCain voters. In other words, Obama has 95% of returning Obama 2008 voters and 5% of returning McCain voters.
Obama has 57.1% with 413 electoral votes.

Scenario II: 90% of Obama 2008 voters turn out in 2012 and 95% of McCain voters turn out. As in Scenario I, there is zero net defection of returning voters.
Obama has 55.9% with 388 electoral votes.

Scenario III: 90% of Obama voters turn out, but he only wins 90% of them. Romney still wins 95% of returning McCain voters. He has a 5% turnout and defection rate advantage.
Obama has 53.5% with 334 electoral votes.

Obama wins all the above scenarios. So what will it take for Romney to win the election?

Scenario IV: The model shows that Romney needs 18% of Obama voters (nearly one in five), He needs a 5% turnout advantage and a 13% net defection advantage.
Romney wins in a squeaker with 50.4% and 280 expected electoral votes.

But if Obama voters turn out at the same 95% rate as McCain voters, Obama wins a squeaker with 50.5% and 275 expected electoral votes.

This analysis is predicated on an equal split in new voters. If history is a guide, new voters will be solidly Democratic, so Obama’s popular and electoral votes will be higher in each of the above scenarios.

That’s why the Republicans are trying to limit new Democratic registrations. GOP governors seek to limit early voting and impose strict voter ID requirements. But the GOP knows that disenfranchising 5 million voters won’t be enough for Romney to win. You see, there is this thing called the red-shift. Otherwise known as the fraud factor. Stay tuned.

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

 
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Posted by on October 6, 2012 in Uncategorized

 
 
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