Richard Charnin
May 15, 2013

An actuary engaged by London Sunday Times calculated 100,000 TRILLION to 1 odds of 18 JFK material witness deaths from Nov. 1963 to Feb. 1967. The House Select Committee on Assassinations (HSCA) incorrectly dismissed the calculation as invalid. The HSCA made a number of fundamental errors:

1) considered just 21 of 46 deaths in the three years, failing to include Oswald, Ruby, Ferrie, etc.
2) did not specify that the deaths were UNNATURAL
3) did not consider witness CONNECTIONS to the case and MOTIVATION for their elimination
4) ignored the need to utilize UNNATURAL MORTALITY RATES
5) falsely stated that the UNIVERSE of witnesses was UNKNOWABLE
6) ignored the KNOWN UNIVERSE of 552 Warren Commission witnesses:14 unnatural, 10 suspicious deaths
7) ignored the SUSPICIOUS deaths in 1977 of 7 top FBI officials called to testify at HSCA
8) did not question why no one at the London Times knew the actuary’s name
9) failed to show the actuary’s ASSUMPTIONS and calculation METHOD
10) did not consider using the POISSON distribution function to calculate probabilities

The HSCA succeeded in misinforming the public by falsely claiming that the actuary’s calculation was invalid and therefore did not prove a conspiracy.

The key to calculating the probability of a given number (n) of unnatural deaths occurring in a given group (N) in a given time period (T) is to recognize that it is based on the difference between expected and actual unnatural deaths. The larger the discrepancy between the actual observed and expected number of deaths, the lower the probability.

These are the relevant probability input parameters:
N= total number of witnesses
n= number of observed unnatural deaths
T= time period in years
R= unnatural mortality rate

These tables in the JFK Witness Spreadsheet Database display unnatural death probabilities for 552 Warren Commission and 1400 material witnesses based on unnatural, weighted and homicide mortality rates over 3, 7 and 14 year time intervals.

In 1963, the annual national homicide rate was 6 per 100,000 (0.00006). At least 4 of the 552 Warren Commission witnesses were murdered in the first 3 years after the assassination. The equivalent Warren Commission rate was 0.0024 =4/(552*3) or 240 per 100,000 (40 times the national rate).

If the 5 accidental deaths and 1 suicide in the three year period were actually homicides, then the equivalent Warren Commission rate was 0.006038 = 10/(552*3) or 603 per 100,000 (100 times the national average).

The Poisson Distribution calculates the probabilities of rare events over time.

We must first calculate E, the expected number of unnatural deaths: E= N*R*T
The probability of EXACTLY n unnatural deaths is: P = POISSON (n, E, false).
The probability of AT LEAST n deaths is P = 1- POISSON (n-1, E, true)

EXAMPLE:
The probability of AT LEAST 14 Warren Commission witness homicides in the 14 years from 1964-77:
E = 0.479 = N*T*R = 552*14*0.000062
P = 1 – Poisson (13, 0.479, true)
P = 4.44E-16 = 1 in 2,251,799,813,685,248
P = 1 in 2251 trillion

According to the reference “Who’s Who in the Kennedy Assassination”, there were approximately 1400 material witnesses connected in any way to the assassination. It is a fact that 552 witnesses testified at the Warren Commission.

The published unnatural mortality rates are:
homicide 0.000062 (in 1963)
suicide 0.000107
accident 0.000359
Unknown 0.000014
Total 0.000542 (unweighted rate)

The unnatural mortality rates used in the probability calculations are:
1) 0.000542 total unweighted rate (national rate – conservative)
2) 0.000163 weighted average rate (based on official cause of JFK witness unnatural death)
3) 0.000062 homicide rate (assumes all suicides and accidents were actually homicides)

Of the 72 unnatural deaths in the 107 JFK-related material witness database, 39 were homicides, 10 suicides and 23 accidents. The weighted unnatural mortality rate is calculated as:
R = 0.000163 = (39 * 0.000062 + 10 * 0.000107 + 23 * 0.000359) / 72

If the JFK unnatural deaths were in the same proportion as the national death rates, the 0.000542 unweighted rate would be the one to use. But the JFK-related deaths were mostly homicides, so the 0.000163 weighted rate is more appropriate – and results in lower probabilities. If we assume all the unnatural deaths were homicides (0.000062), the probabilities are at their lowest.

Probability of AT LEAST 10 Warren Commission unnatural witness deaths over 3 years:
1) unweighted: 3.0E-08 (1 in 33 MILLION); Expected = 0.87
2) weighted: 4.4E-13 (1 in 2.2 TRILLION); Expected = 0.27
3) homicide: 3.2E-17 (1 in 31,000 TRILLION vs. actuary 1 in 100,000 TRILLION); Expected = 0.1

Probability of 72 unnatural deaths of 1,400 material witnesses over 14 years:
1) unweighted: 3.9E-36 (1 in a TRILLION TRILLION TRILLION); Expected = 10.27
2) weighted: 1.4E-69 (1 in a TRILLION TRILLION TRILLION TRILLION TRILLION); Expected = 3.19
3) homicide: 6.0E-99 (1 in a TRILLION TRILLION TRILLION TRILLION TRILLION TRILLION TRILLION TRILLION); Expected = 1.22

For Warren Commission advocates who believe the universe of witnesses exceeds 1,400, the probability of 72 unnatural deaths OVER 14 YEARS assuming 10,000 material witnesses:
1) unweighted: 4.6E-02 (1 in 22); Expected = 74
2) weighted: 1.3E-16 (1 in 8,000 TRILLION); Expected = 23
3) homicide: 1.0E-40 (1 in 9,000 TRILLION TRILLION TRILLION); Expected = 9

That’s all there is to it.

Richard Charnin
April 24, 2013
Updated: May 9, 2013

This probability analysis focuses on the 24 unnatural and suspicious deaths of 552 Warren Commission witnesses. It covers the first three years after the assassination and the 14 year period from 1964-1977. The 24 deaths are a subset of at least 100 JFK-related witnesses who died unnaturally or suspiciously and are included in the JFK witness spreadsheet database.

This is a table of Warren Commission witnesses who died unnaturally or suspiciously in 1964-1977.

At least fourteen deaths were unnatural: 3 suicides, 4 homicides, 1 attempted murder and 6 accidents. The suicides were most likely homicides: Roger Craig supposedly shot himself after surviving several attempts on his life. George De Morenschildt supposedly shot himself the same day he was called to give testimony at the House Select Committee on Assassinations (HSCA). Albert Bogard supposedly committed suicide from carbon monoxide. He was badly beaten after giving testimony. The six accidents were also most likely homicides.

The other ten deaths were suspicious: Jack Ruby and Frank Martin had sudden cancers within one month after being diagnosed. Edward Voebel, a classmate of Oswald, died from a mysterious blood clot. The others (3 heart attacks and 4 deaths from natural causes) were suspicious; some were due to testify.

This analysis confirms the actuary’s odds over 3 and 14 year periods using weighted and unweighted UNNATURAL rates. The probability of 10 Warren Commission HOMICIDES in the 3 years following the assassination is 1 in 31,000 TRILLION. The probability of at least 14 HOMICIDES in the 14 years from 1964 to 1977 is 1 in 2,000 TRILLION.

The mathematical proof closes the book on those who still promote the fiction that Oswald was the lone assassin. The few remaining defenders of the Warren Commission’s Magic Bullet Theory have tried mightily for nearly 50 years to dismiss the mathematical significance of the mysterious deaths of JFK-related witnesses – starting with Ruby shooting Oswald. After all, a “clean-up” operation would only occur in a conspiracy. Of course, Warren Commission apologists claim that Oswald was a lone nut who acted alone. But these “lone-nutters” must know that dead men like Jack Ruby (“sudden cancer”) and dead women like reporter Dorothy Kilgallen (“suicide”) tell no tales.

The basis of the lone nut “argument” has been to claim that 1) the dead witnesses were of minor or no importance and that 2) the universe of total witnesses was ultimately unknowable. But they ignore the fact that the Warren Commission considered the witnesses important enough to have them testify.

The “universe” of 552 Warren Commission witnesses is obviously a known quantity. Therefore, given the actual number and cause of the unnatural and suspicious deaths (and corresponding mortality rates), we have all the information needed to calculate the probability that they would occur in a given time interval. But the 24 Warren Commission witnesses are just one part of the story.

At least 48 of the 107 witnesses listed in the database of unnatural and suspicious deaths were called to testify in four investigations and were obviously relevant: 24 testified at the Warren Commission, 12 were sought by prosecutor Jim Garrison at the Clay Shaw trial, 4 by the Senate Intelligence Committee, 17 by the House Select Committee on Assassinations (HSCA). Nine witnesses were called in two investigations. Of the 107, 72 died unnaturally (homicides, suicides, accidents) while 35 were highly suspicious heart attacks, sudden cancers, etc.

Given the 0.00016 weighted average unnatural mortality rate, the probability that these 48 witnesses would meet unnatural or suspicious deaths (assuming 1400 material witnesses) is P = 2.6E-39 (less than 1 in a TRILLION TRILLION TRILLION). To be conservative, assume the 0.000542 unweighted unnatural mortality rate. The probability is 1 in 28,000 TRILLION.

The 1973 film Executive Action depicted a conspiracy to assassinate JFK and revealed that an actuary engaged by the London Sunday Times calculated the probability of 18 material witnesses dying within three years of the JFK assassination as 1 in 100,000 TRILLION.

In this video, Mark Lane, famous author/investigator of several books on the assassination, interviews Penn Jones, an independent researcher of JFK witness deaths.

The probability analysis is straightforward; it is not a theoretical exercise. It is a mathematical proof of conspiracy based on factual data (552 total witnesses, at least 14 unnatural deaths, corresponding mortality rates) and the Poisson probability formula. The numbers and probabilities speak for themselves. This is a challenge to those who still claim that the deaths do not prove a conspiracy: To substantiate your claim, you must refute the data (i.e., the Warren Commission witness list), the unnatural mortality rates and the use of the Poisson formula.

Hit List: An In-Depth Investigation into the Mysterious Deaths of Witnesses to the JFK Assassination by Richard Belzer and David Wayne, is a unique and welcome addition to the massive trove of JFK Assassination literature. The authors cite my probability analysis as background information.

The Warren Commission witnesses who testified comprise a subset of approximately 1400 material witnesses who were related in any way to the assassination (police, reporters, eyewitnesses, FBI officials, CIA contacts, anti-Castro Cubans, Ruby and Oswald contacts, etc.). A comprehensive analysis is provided in Executive Action: JFK Witness Deaths and the London Times Actuary.

This graph shows the long-term trend in the U.S. homicide rate. Note that in 1963 the rate was approximately 6 per 100,000 (0.000062 is used in the homicide probability calculation).

1964-1966
There were 11 suspicious deaths of Warren Commission witnesses: 3 homicides, 1 attempted murder, 1 suicide, 3 motor accidents, 2 sudden cancers, 1 heart attack. Consider just the 8 official unnatural deaths (homicides, accidents and suicide). The weighted average mortality rate is 0.000179. The probability is 1 in 910 MILLION.

Assuming the 8 deaths were homicides,the probability is 1 in 3.6 TRILLION. But the two sudden cancers were likely homicides. If the 10 UNNATURAL deaths were homicides, the probability is 1 in 31,000 TRILLION. This is in the same ballpark as the actuary’s 1 in 100,000 TRILLION ODDS of 18 material witness deaths in three years.

1964-1977
There were 24 suspicious deaths of Warren Commission witnesses. Fourteen died unnaturally: 5 homicides, 3 suicides, 6 accidental. The others were sudden cancers and heart attacks. Only 1.5 unnatural deaths would normally be expected over the 14 year period. Using the weighted 0.0002 mortality rate, the probability is 1 in 1 BILLION. If the suicides and accidents were actually HOMICIDES, the probability is 1 in 4,000 TRILLION.

1400 JFK-related witnesses

In 1964-1977, at least 72 material witnesses died unnaturally (39 homicides, 10 suicides, 23 accidental). Applying the total unnatural mortality rate (0.000542) the probability is 3.1E-35. That is less than ONE in a BILLION TRILLION TRILLION.

Using the actual observed weighted unnatural rate (0.000163), the probability of 72 unnatural deaths is 1.4E-69. That is less than ONE in a TRILLION TRILLION TRILLION TRILLION TRILLION.

Warren Commission apologists have suggested that there were many more than 1400 material witnesses and therefore the probabilities are not valid – without providing a list. To refute this canard, we calculate the probabilities assuming 10,000 material witnesses using the 0.000163 weighted unnatural mortality rate.

The probability of 72 unnatural deaths in 1964-77 is 1.3E-16 (1 in 8,000 TRILLION).
The probability that 34 witnesses would die unnaturally in the three years following the assassination is 7E-18 (1 in 140,000 TRILLION).

To put the magnitude of the numbers in context, consider that there are 60 TRILLION TRILLION (6E25) hydrogen atoms in a quart of water, approximately 700,000 TRILLION (7E17) grains of sand on the earth and 300 BILLION TRILLION (3E23) stars in the universe.

The probability of exactly n deaths among N witnesses over T years given mortality rate R is calculated using the Poisson spreadsheet function:
P (n) = Poisson (n, N*T*R, false)

The probability of at least n deaths is
P (n) = 1 – Poisson (n-1, N*T*R, true)

The probability of at least 14 Warren Commission homicides in the 14 year period (0-1 expected) is
P (>=14) = 1- Poisson (13,552*14*0.000062, true)
P = 1 in 2,251,799,813,685,248 (1 in 2251 trillion)

Hit List: An In-Depth Investigation into the Mysterious Deaths of Witnesses to the JFK Assassination by Richard Belzer and David Wayne, is a unique and welcome addition to the massive trove of JFK Assassination literature.

There is no conjecture here, just the facts surrounding fifty mysterious witness deaths presented in an easy-to-read format. Warren Commission apologists are reduced to irrelevancy; the proof of conspiracy is overwhelming and beyond any doubt. The authors cite my probability analysis as background information.

The 1973 film Executive Action depicted a conspiracy to assassinate JFK and revealed that an actuary engaged by the London Sunday Times calculated the probability of 18 material witnesses dying within three years of the JFK assassination as 1 in 100,000 TRILLION.

In this video, Mark Lane, famous author/investigator of several books on the assassination, interviews Penn Jones, an independent researcher of JFK witness deaths.

Assuming the data and calculation methodology were essentially correct, then it was clear proof of a conspiracy and refuted the Warren Commission’s conclusion that Oswald was the lone assassin. A comprehensive probability analysis shows that the actuary’s odds were conservative. There were many more than 18 suspicious deaths.

The proof is in the post Executive Action: JFK Witness Deaths and the London Times Actuary which links to the JFK Witness Database Spreadsheet Model.

The probability analysis is straightforward; it is not a theoretical exercise. It is a mathematical proof of conspiracy based on factual data (552 Warren Commission witnesses, at least 14 unnatural deaths, corresponding mortality rates) and the Poisson probability formula. The numbers and probabilities speak for themselves. This is a challenge to those who still claim that the deaths do not prove a conspiracy: To substantiate your claim, you must refute the data (i.e., the Warren Commission witness list), the unnatural mortality rates and the use of the Poisson formula.

There were approximately 1400 JFK-related witnesses. In 1964-1977, at least 70 died unnaturally (homicide, suicide, accidental, unknown) and 34 deaths were suspiciously timed heart attacks, cancers, etc. Normally 11 unnatural deaths would be expected.

Some have questioned the relevance of the unnatural and suspicious witness deaths related to the assassination. There are 71 unnatural deaths out of the 107 deaths in the spreadsheet database. Of the 107, 24 testified at the Warren Commission, 12 were sought or testified at the Clay Shaw trial by prosecutor Jim Garrison, 4 by the Church Senate Committee, 17 by the House Select Committee on Assassinations (HSCA). Of the 57, 9 testified or were sought to testify by two of the four groups. Therefore, at least 48 witnesses in the database of 107 are indisputably relevant.

What are the odds that 48 witnesses called to testify (out of 1400 material witnesses) would meet unnatural deaths- before OR after testifying?
P= 2.67E-39 (less than 1 in a TRILLION TRILLION TRILLION).

The probability of exactly n deaths among N witnesses over T years given mortality rate R is calculated using the Poisson function: P (n) = Poisson (n, N*T*R, false)

The probability of at least n deaths is P (n) = 1- Poisson (n-1, N*T*R, true)

The following table displays the unnatural cause of death and corresponding mortality rate, expected number of deaths among the 1400 JFK witnesses, the actual number of deaths, and the probability.

Cause……..rate; expected; actual; probability
suicide……. 0.000107; 2.1; 7; 1 in 170
homicide…. 0.000062; 1.2; 40; 1 in 1 BILLION TRILLION TRILLION TRILLION
accidental.. 0.000359; 7.0; 23; 1 in 2.3 MILLION
unknown… 0.000014; 0.3; 5; 1 in 5 THOUSAND

TOTAL UNNATURAL..0.000542; 10.6; 70; 1 in 700 MILLION TRILLION TRILLION

To those who say there were many more than 1400 material witnesses, which means the probabilities are too low, consider 10,000 witnesses and 72 unnatural deaths from 1964-77. The probability is 1.3E-16 or 1 in 8,000 TRILLION, very close to the Sunday London Times actuary. For 3 years and 34 unnatural deaths, it is 7E-18 or 1 in 40,000 TRILLION.

This graph shows the long-term trend in U.S. homicide rate. Note that in 1963 the rate was approximately 6 per 100,000 (0.000062 is used in the homicide probability calculation).

Assuming 1400 JFK-related witnesses and the mortality rates above, the probability of at least
- 15 UNNATURAL deaths within ONE year of the assassination: 1 in 167 TRILLION.
- 33 UNNATURAL deaths within THREE years: less than 1 in 100 TRILLION TRILLION.
- 70 UNNATURAL deaths from 1964-77: 1 in 700 MILLION TRILLION TRILLION.
- 40 HOMICIDES from 1964-77: 1 in a BILLION TRILLION TRILLION TRILLION.

Of the 552 Warren Commission witnesses, there were at least fourteen unnatural deaths: 3 suicides, 5 homicides and 6 accidents. Nine others were suspicious. The probability of at least 22 UNNATURAL/SUSPICIOUS deaths and 1 attempted murder is 1 in 7 BILLION. If the “suicides” and “accidents” were actually HOMICIDES, then the probability of at least 14 HOMICIDES among the 552 witnesses is 1 in 2 THOUSAND TRILLION.

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)

Richard Charnin

http://richardcharnin.com/

Feb. 25, 2013
Updated April 14, 2013

The 1973 film Executive Action depicted a conspiracy to assassinate JFK. It was based on a book by Mark Lane, who in 1966 was the first JFK investigator to debunk the Warren Commission in his book Rush to Judgment. Burt Lancaster and Robert Ryan played CIA operatives involved in the plot. They were resisted in their efforts to have the film made by mainstream Hollywood producers. The movie reveals how Kennedy’s progressive agenda and peace initiatives were a threat to the establishment. He refused to invade Cuba, was seeking detente with the Soviet Union, planned to pull all troops out of Viet Nam by 1965, break up the CIA, eliminate the Federal Reserve and promoted the civil rights movement. Congress passed the Test Ban Treaty a few months before the assassination. In other words, he was doing his job.

At the end of the film, it was revealed that an actuary engaged by the London Sunday Times calculated the odds of 18 material witnesses dying within three years of the JFK assassination. as 1 in 100,000 TRILLION. Assuming the data and calculation methodology were essentially correct, then it was clear proof of a conspiracy and refuted the Warren Commission conclusion that Oswald was the lone assassin.

In this video, Mark Lane, famous author/investigator of several books on the assassination, interviews Penn Jones, an independent researcher of JFK witness deaths.

There has been much controversy about the actuary’s calculation. Apparently, no one at the Sunday Times even remembers the actuary’s name. And even more strange, the Times editor did not provide the 1977 House Select Committee on Assassinations (HSCA) the actuary’s calculation assumptions or methodology. The editor claimed that the problem was not clearly defined and therefore the calculation of the odds was suspect. This analysis indicates that the calculation was essentially correct – and that the editor’s response to HSCA was misleading and incomplete.

In fact, there were more than 18 suspicious deaths in the three years following the assassination. The actuary did not include Oswald and Ruby – and at least 20 others. The JFK witness spreadsheet database shows there were at least forty (40) suspicious deaths in the three years; at least 33 were unnatural (homicide, accident, suicide, unknown). The probability of 33 unnatural deaths is lower than 1 in 100 TRILLION TRILLION!

The probability of at least 70 unnatural deaths in the 14 years following the assassination is 1 in 714 MILLION TRILLION TRILLION (1.4E-33). . There were at least 100 unnatural and suspicious deaths, so the probability must be even lower. Since the probability of 70 deaths is infinitesimal, why bother to look any further?

Some have questioned the relevance of the unnatural and suspicious witness deaths related to the assassination. . Of the 107 in the database, 24 testified at the Warren Commission, 12 were sought at the Clay Shaw trial by prosecutor Jim Garrison, 4 by the Church Senate Committee, 17 by the House Select Committee on Assassinations (HSCA). Of the 57 total, 9 were sought by two of the four groups. Therefore, at least 48 witnesses in the database are indisputably relevant.

What is the probability that 48 of 1400 material witnesses would meet unnatural deaths (assuming the 0.000163 weighted average mortality rate)?
P= 2.6E-39 (less than 1 in a TRILLION TRILLION TRILLION).

What is the probability of 40 homicides among the 1400 witnesses (assuming the 0.000062 homicide rate)?
P= 8.8E-46 or 1 in a BILLION TRILLION TRILLION TRILLION.

Warren Commission apologists have suggested that there were many more than 1400 material witnesses and therefore the probabilities are not valid – without providing a list. To refute this canard, we calculate the probabilities assuming 10,000 material witnesses using the 0.000163 weighted unnatural mortality rate.

The probability of 72 unnatural deaths in 1964-77 is 1.3E-16 (1 in 8,000 TRILLION).
The probability that 34 witnesses would die unnaturally in the three years following the assassination is 7E-18 (1 in 140,000 TRILLION).

Perhaps the problem is better illustrated if we ask: How many unnatural deaths are required in the 14 year period (assuming 1400 material witnesses) to obtain a probability of less than 1% (ONE in ONE HUNDRED)? This would meet the definition of beyond a reasonable doubt. The answer is 18. How many would return a probability of ONE in ONE THOUSAND? The answer is 22. As the number of deaths increase, the probability rapidly approaches ZERO.

HSCA statistical expert Jacqueline Hess testified that the actuarial calculation was “invalid” due to the “impossibility” of defining the “universe” of material witnesses. Her dismissal of the odds was a ruse (like the Magic Bullet Theory) to maintain the cover-up.

The fact is that there was a definable set of 552 Warren Commission witnesses. At least 20 died unnaturally in the period from 1964-1977. Only four would normally be expected.. But two others should be included. Domingo Benavides was a witness to the Tippit murder who could not identify Oswald. He changed his testimony after his brother was shot and identified Oswald. Warren Reynolds was a witness at the Tippit scene. He changed his testimony after making a miraculous recovery from a gunshot to the head.

Of the 552 Warren Commission witnesses, the probability of at least 22 UNNATURAL/SUSPICIOUS deaths and 1 attempted murder in the 1964-77 period is 1 in 7 BILLION. Three deaths were classified as suicides, 5 as homicides and 6 accidental. If the “suicides” and “accidents” were actually HOMICIDES, then the probability of at least 14 HOMICIDES is 1 in 2 THOUSAND TRILLION.

The 552 witnesses can be viewed as a subset of the approximately 1400 JFK-related witnesses named in the reference Who’s Who in the JFK Assassination.

The probability analysis is straightforward; it is not a theoretical exercise. It is a mathematical proof of conspiracy based on factual data (552 Warren Commission witnesses, at least 14 unnatural deaths, corresponding mortality rates) and the Poisson probability formula. The numbers and probabilities speak for themselves. This is a challenge to those who still claim that the deaths do not prove a conspiracy: To substantiate your claim, you must refute the data (i.e., the Warren Commission witness list), the unnatural mortality rates and the use of the Poisson formula.

This graph shows the long-term trend in U.S. homicide rate. Note that in 1963 the rate was approximately 6 per 100,000 (0.000062 is used in the homicide probability calculation).

There were different categories of witnesses: 1) The 121 eyewitnesses who gave depositions to the FBI (51 said the shots came from the front, 38 from the rear, 32 were unsure); 2) the 552 interviewed by the 1964 Warren Commission; 3) witnesses sought by Jim Garrison 3) witnesses sought by the HSCA; and 4) the full set of 1400+ JFK-related witnesses.

The timing of the deaths makes it all the more suspicious. At least fifteen died the year after the assassination; several died in 1967, soon after being named as witnesses in the 1969 Garrison/Shaw trial; at least 12 died in 1977 (including SEVEN FBI officials) just before they were due to testify at HSCA. Using this information, we can calculate probabilities of these unnatural, suspicious deaths for each witness category.

Hit List: An In-Depth Investigation Into the Mysterious Deaths of Witnesses to the JFK Assassination is a comprehensive study by Richard Belzer and David Wayne (published April 2013).

The following graph displays the probability of a range of unnatural deaths for 552 Warren Commission witnesses from 1964-1977. The probability declines to ZERO at 12 deaths.

But even the “natural” deaths were suspicious: heart attacks, sudden cancers, etc. Jack Ruby died just before his second trial, 29 days after being diagnosed with cancer. He claimed that he was injected with a virus.

Another mysterious death was David Ferrie who supposedly had a brain aneurysm that was ruled a suicide – the day after his release from protective custody. He had just been named as a witness by New Orleans D.A. Garrison in the Clay Shaw trial.

In spite of their efforts, the HSCA was forced in a “limited hangout” to conclude that both the JFK and Martin Luther King murders were conspiracies. Acoustic evidence indicated a 96% probability that at least four shots were fired. At least one came from the grassy knoll, indicating at least two shooters. That should have closed the book on the Warren Commission’s physically impossible, irrational Magic Bullet Theory but this 50-year old work of fiction is still presented as gospel by the mainstream media while the overwhelming scientific ballistic, acoustic, video, medical, eyewitness and mathematical evidence of suspicious deaths is ignored.

The mathematical analysis of the scores of suspicious, unnatural deaths related to the assassination is further proof of a conspiracy – beyond any doubt. This is a comprehensive spreadsheet database of suspicious unnatural witness deaths, probability calculations, Warren Commission, Garrison/Shaw trial and HSCA witnesses.

The London Times

In a response to a letter from the 1977 House Select Committee on Assassinations, London Sunday Times Legal Manager Anthony Whitaker wrote: Our piece about the odds against the deaths of the Kennedy witnesses was, I regret to say, based on a careless journalistic mistake and should not have been published. This was realized by The Sunday Times editorial staff after the first edition – the one which goes to the United States – had gone out, and later editions were amended. There was no question of our actuary having got his answer wrong: it was simply that we asked him the wrong question. He was asked what were the odds against 15 named people out of the population of the United States dying within a short period of time to which he replied -correctly – that they were very high. However, if one asks what are the odds against 15 of those included in the Warren Commission Index dying within a given period, the answer is, of course, that they are much lower. Our mistake was to treat the reply to the former question as if it dealt with the latter – hence the fundamental error in our first edition report, for which we apologize. None of the editorial staff involved in the story can remember the name of the actuary we consulted, but in view of what happened, you will, I imagine, agree that his identity is hardly material.

The actuary’s identity was hardly material? It was and still is very material. Only the actuary could speak to his interpretation of the problem and method of calculation. And no one on the editorial staff remembered his name? Really? We are supposed to believe that? Both statements made no sense; nothing else the Times editor said should have been taken at face value. In fact, Whitaker misrepresented what is essentially a simple mathematical problem: to determine the probability of a given number of unnatural deaths over relevant time intervals within a given population group.

His first error was to provide an incomplete and misleading statement of the problem. The U.S. population is not relevant; the number of JFK-related witnesses is. The “short period of time” is not specific. He misrepresented the essential goal of the probability analysis by not considering the frequency of unnatural deaths.

His second error was one of omission. He did not provide unnatural death mortality statistics and probability calculations used by the actuary. Was it because they would show that the calculation was plausible?

Whitaker claimed that he asked the actuary to calculate the probability that 15 names included in the Warren Commission Index would die within a “short” period. One must assume that the actuary assumed unnatural deaths and utilized corresponding unnatural mortality rate(s) in his calculation. Just because the Times Editor did not specify unnatural deaths does not mean that the actuary was oblivious to the distinction. Is it just a coincidence that at least 15 Warren Commission witnesses (listed below with links to their testimony) died unnaturally and/or suspiciously. Or that others died mysteriously at convenient times just before they were due to give testimony at the Garrison/Shaw trial or at the HSCA?

It is important to note that Whitaker did not specify unnatural deaths – as he should have. In any case, his response settled the matter. The HSCA’s designated “statistical expert” just added to Whitaker’s obfuscation.

HSCA Obfuscation

The HSCA designated statistical expert Jacqueline Hess dismissed the actuary’s odds as being invalid, claiming that it was “unsolvable”. Hess testified that she consulted with actuarial experts, who told her “you cannot establish any kind of universe” of material witnesses. This was pure disinformation; a universe of 1400+ JFK-related witnesses was presented in the Who’s Who in the Kennedy Assassination reference.

And there were exactly 552 witnesses who testified before the Warren Commission. At least 14 died unnaturally and 10 suspiciously from heart attacks and sudden cancers in the 1964-77 period.. The probability of 14 homicides is 1 in 4000 TRILLION.

In her list of 21 names, Hess conveniently left out scores of mysterious, unnatural deaths. She focused on five names in the list where the deaths appeared to have been natural (heart attacks). But they were still suspicious.

For example, Thomas Howard was one of three people who met in Ruby’s apartment on Nov. 24, 1963. All died in a little over a year (two unnaturally). Hess never calculated the odds.

She did not include David Ferrie and Eladio del Valle. Ferrie supposedly died of an aneurysm within days of being called as a witness by Garrison. Ferrie was held in protective custody until Feb. 21, 1967. He was found dead in his apartment the next day. Ferrie associate Eladio del Valle was also sought by Garrison. He was murdered on Feb. 21. Hess never calculated those odds, either.

What is even more unbelievable, Hess neglected the strange deaths of a dozen prospective HSCA witnesses. She gave a convoluted excuse as to why she did not include George De Morenschildt, Oswald’s friend who allegedly shot himself with a rifle the day he was notified by HSCA.

Nor did she mention the seven (7) high level FBI officials who died within a six-month period in 1977 just before they were due to testify at HSCA. The probability is ZERO. Apparently, HSCA-related deaths were immaterial. But even the 1964-1967 analysis was incomplete.

Hess claimed that the actuary concluded that on 11/22/63 the odds of 15 witnesses being dead in three years was 1 in 10 to the 29th power (1 in 10,000 TRILLION TRILLION). That is obviously an incorrect statement. The actuary calculated the odds as 1 in 100,000 trillion (1 in 10 to the 17th power). He presumably used the Poisson probability function of rare events – the perfect mathematical tool for the problem (see below). One in 100,000 trillion is E-17, or 0.0000000000000001. Hess appears to have been anything but a “statistical expert”. If she was one, she would have done the calculations herself.

So how did the actuary calculate the probability? If he assumed 560 witnesses, consisting of the 552 who testified at the Warren Commission (10 died unnaturally) and 8 other JFK-related witnesses who died unnaturally, then applying the 0.000542 unnatural mortality rate, the probability of exactly 18 unnatural deaths in three years is 1.16E-17 or 1 in 85 thousand trillion. This is very close to the actuary’s 1 in 100,000 trillion odds! Only ONE unnatural death out of the 560 would normally be expected in the three year period.

Bugliosi’s Calculation

Famed prosecutor Vincent Bugliosi tried to refute the actuary in his book Reclaiming History: The Assassination of President John F. Kennedy. He cited Robert M. Musen, vice president and senior actuary at Metropolitan Life Insurance Company. Musen calculated the odds of 15 people out of 2,479 in the Warren Commission Index dying within a three-year period, assuming a median age of 40, to be 98.16 percent or one out of 1.2.

But there are two major problems with Musen’s calculation.
1- There are only approximately 600 names listed in the index, including George Washington and several other presidents. Only 552 were witnesses who testified.

2- Musen did not consider that the deaths were unnatural. Even assuming 2479 names, approximately 4 unnatural and 70 natural deaths from the list would be expected over a three year period. Musen must have applied an approximate .01 overall mortality rate, not the .000542 unnatural rate.The odds that at least 15 of 2479 would die unnaturally within 3 years is 1 in 46,000. The odds of 18 dying unnaturally is 1 in 3.6 million.

The Correct Method: Expected and Actual Unnatural Deaths

There were 1400 JFK-related witnesses listed in the Who’s Who in the JFK Assassination by Michael Benson At least 15 died from unnatural causes in the first year, defying the odds. There had to be a plausible explanation; the 15 unnatural deaths could not have been just a 1 in 167 TRILLION coincidence. Only one unnatural death would normally be expected. There must have been a rationale and motivation for the deaths. What could it have been?

Of the 1400 witnesses, at least 70 died unnaturally (homicide, suicide, accidental, unknown) from 1964-1977 and another 34 were suspiciously timed heart attacks, cancers, etc. Normally 11 unnatural deaths would be expected.

Cause……..rate; expected; actual; prob
suicide……. 0.000107; 2.1; 7; 1 in 170
homicide…. 0.000062; 1.2; 40; 1 in 1 BILLION TRILLION TRILLION TRILLION
accidental.. 0.000359; 7.0; 23; 1 in 2.3 MILLION
unknown… 0.000014; 0.3; 5; 1 in 5 THOUSAND
TOTAL UNNATURAL..0.000542; 10.6; 70; 1 in 714 MILLION TRILLION TRILLION

Assuming 1400 JFK-related witnesses and using the mortality rates above, the probability of at least
- 15 UNNATURAL deaths within ONE year of the assassination: 1 in 167 TRILLION.
- 33 UNNATURAL deaths within THREE years: less than 1 in 137 TRILLION TRILLION.
- 70 UNNATURAL deaths from 1964-77: 1 in 714 MILLION TRILLION TRILLION.
- 40 HOMICIDES from 1964-77: 1 in a BILLION TRILLION TRILLION TRILLION.

The expected number N of unnatural deaths in time period T is approximated by a simple formula: N = R * W * T, where R is the unnatural mortality rate, W the number of witnesses and T the number of years in the study. For one year, N = 0.76 deaths = .000542*1400*1

The Poisson Probability Distribution

The Poisson function is useful for calculating the probability that a certain number of rare events will occur over a specified period of time. For instance, the probability that 10 customers will walk into a store from 10-11 am, given an average arrival rate of 5 per hour for that time period. Or that 2 accidents will occur at a busy intersection next month, given an average of 1 per month.

In the JFK analysis, the Poisson function is used to calculate the probability that a number of witnesses would die unnaturally (suicide, murder, accident, unknown cause, etc.) over various time periods. Historical mortality statistical tables show that the unnatural death rate R is approximately 0.000542 (1 in 1845).

The Poisson probability function is:
P(n) = a^n * exp(-a)/n!
where a = the expected number of unnatural deaths = R*N*T

For example, in a random group of 1400 individuals, in any given year less than ONE unnatural death (0.7588) is expected to occur: a = 0.7588 = R*N*T = 0.000542*1400*1

Using the expected number (a=.7588) of unnatural deaths and the actual number (n= 15) in the Poisson formula, the probability that there would be exactly 15 unnatural deaths turns out to be
P (15) = 0.7588^15 * exp(-0.7588)/15!
P (15) = 5.70E-15 = 1 in 175 trillion

The probability of at least 15 unnatural deaths is of course slightly higher: P (>=15) = 1 in 167 trillion!

Key witness categories
1 Unnatural deaths vs. suspicious natural deaths
2 Witnesses: Warren Commission (552), Shaw trial (60), HSCA (100)
3 Witnesses who died just before being called to testify (15+)
4 Approximate number of JFK-related witnesses (1400+)
5 Eyewitness depositions to the Warren Commission (121)

- The unnatural death rate is used in the probability analysis.
- ZERO probability of unnatural deaths in categories 2,3 and 4.
- 51 Warren Commission eyewitnesses claimed that the shots came from the Grassy Knoll, 38 from the Texas Schoolbook Depository and 32 had no opinion. Their recollections were dismissed by the Warren Commission as simply being “mistaken”. Parkland Hospital doctors initially reported entrance wounds to the neck and head which were confirmed years later in the Zapruder film.

Ruby’s Visitors

Ruby shot Oswald on Nov. 24, 1963. But how many know that three people who met in Ruby’s apartment that day died within one year, two unnaturally and one naturally. The probability is
P = 1/(.000542^2*.01)= 1 in 340 million!

- Bill Hunter, a reporter, was shot to death by a policeman in April 1964. It was ruled an accident.
- Tim Koethe, another reporter, was killed in Sept. 1964 by a blow to the neck.
- Tom Howard, Ruby’s first lawyer, died from a heart attack in March 1965.

Mysterious FBI Witness Deaths

In 1977, seven top FBI officials died in a six month period just before they were scheduled to testify at the House Select Committee on Assassinations(HSCA). Two were accidents. If we assume only 7 FBI were called to testify and all died from natural causes within a six month period, the probability is 1 in 81 TRILLION. But the odds must be lower than that since at least two of the deaths were unnatural “accidents”.

. William Sullivan- Head of counter/espionage. Predicted his death. Hunting accident.
. James Cadigan- Document expert; previously testified to Warren Commission. Accidental fall in his home.
. Regis Kennedy- Heart attack on the day he was to testify on confiscation of home movies of assassination.
. Louis Nichols- Former #3, worked on JFK investigation. Heart attack
. Alan Belmont- Liaison to Warren Commission; Long illness.
. Donald Kaylor Fingerprint expert. Heart attack.
. J.M. English- Head of Forensic Sciences Lab. Heart attack.

Suspicious Timing of Other Witness Deaths

In 1967, David Ferrie was found dead (ruled a suicide from a brain aneurysm) in his apartment shortly after he was named as a defendant by New Orleans D.A. Jim Garrison in the upcoming trial of Clay Shaw. Ferrie was an associate of Oswald, Shaw, Guy Banister and anti-Castro Cubans. Ferrie left two suicide notes. He was held in protective custody until Feb. 21, 1967 and was found dead in his apartment the next day. Ferrie associate Eladio del Valle was also sought by Garrison. He was murdered on Feb. 21 by gunshot and struck in the head by an axe. The odds of both deaths: 1 in 453 billion: P= 1/(0.000542/365)^2. Banister, an ex-FBI agent, died in 1964 from a suspicious heart attack.

Shaw was a New Orleans businessman accused of involvement in the JFK assassination. He denied he was CIA and acquitted. He died a few years later from cancer. There was no autopsy. CIA Director Richard Helms later admitted under oath that Shaw was a CIA contractor.

Maurice Gatlin, also sought by Garrison, was a pilot who worked for Guy Banister, an ex-FBI agent in New Orleans connected to Ferrie, CIA, Carlos Marcello and Oswald. Gatlin died in a fall from the 6th floor after suffering a “heart attack”. The death was ruled an accident.

The following individuals were sought by the HSCA. All died unnaturally. Once again, the probability is ZERO…
- Charles Nicoletti, mob hit man and possible JFK shooter, was found dead from gunshots the day before he was scheduled to be contacted.
- John Paisley, Deputy Director of the CIA, was “about to blow the whistle” (shotgun ruled suicide).
- George DeMohrenschildt, a friend of Oswald with CIA contacts, had previously testified at the Warren Commission. He was found dead the day before he was scheduled to be contacted (shotgun ruled a suicide).
- Johnny Roselli, a powerful Mafia figure, was found in a drum off the coast of Miami. He told investigative reporter Jack Anderson that Ruby was ordered to silence Oswald and testified before the Senate.

Data Sources
The reference Who’s Who in the JFK Assassination by Michael Benson, presents vital information on each of more than 1,400 individuals (from suspects to witnesses to investigators) related in any way to the murder of President John F. Kennedy on November 22, 1963. Based on years of research, it uses a wealth of data sources and a detailed analysis of the Warren Commission’s twenty-six volumes. The volume includes entries on virtually all suspects, victims, witnesses, law enforcement officials and investigators involved in the assassination.

In Crossfire assassination researcher Jim Marrs lists 103 individuals related to the assassination who died mysteriously from 1963-1978. Lee Harvey Oswald is not on the list but should be.

Warren Commission apologists who troll the online forums jump through illogical hoops in their attempts to debunk the probability calculations. But their arguments just prove the case for conspiracy. They agree that the math is correct, but argue that the data is invalid. They claim that the 1400+ witnesses and scores of unlikely deaths were self-selected and not a random group. Of course it is not a random group – by definition. That is precisely the point.

Witnesses who were called to testify before the 1964 Warren Commission, the 1969 Clay Shaw trial and the 1977 HSCA investigation were obviously not self-selected. Neither were the 1400 in the “Who’s Who” reference; they were all related in some way to the JFK assassination – suspects, victims, witnesses, law enforcement officials and investigators. It is not just a coincidence that an impossible number of them died unnaturally. There are only a few dozen that were missed in the “Who’s Who”, but even some of these died unnaturally. The only rational conclusion is that the JFK-related witnesses had information that would lead to the perpetrators.

PROBABILITY CALCULATIONS
N witnesses, at least n unnatural deaths, T years, P odds
Warren Commission: N= 552, n=21 (exact), T= 14, P = 1 in 236 million
Who’s Who Reference: N= 1400, n>=15, T= 1, P = 1 in 167 trillion
Who’s Who Reference: N= 1400, n=33 (exact), T= 3, P = 137 trillion trillion
HSCA: N= 42 (7 FBI+ 35 others), n=7 (assume all natural), T= 6 months, P = 1 in 345 million

1400 JFK-related Witnesses
T = 3 years
p = 0.000542 = unnatural mortality rate
n = 33 unnatural, suspicious deaths; Expected a= 2.3 = p*N*T
P(33) = a^n * exp (-a)/n! = 7.3E-27
P = 1 in 137,439,196,231,656,380,000,000,000
1 in ONE HUNDRED THIRTY-SEVEN TRILLION TRILLION

To put these numbers in perspective, there are approximately 7E17 (700,000 trillion) grains of sand on the earth and 3E23 (300 billion trillion) stars in the universe.

TESTIMONY OF WARREN COMMISSION WITNESSES

Alphabetical List of Witnesses and Testimony

http://jfkassassination.net/russ/wit.htm

Jack Ruby died 28 days after being diagnosed with cancer in prison. He claimed that he was injected with cancer cells. In this press conference, Ruby claimed a government conspiracy to murder JFK.

Ruby said:
“Everything pertaining to what’s happening has never come to the surface. The world will never know the true facts, of what occurred, my motives. The people had- that had so much to gain and had such an ulterior motive for putting me in the position I’m in, will never let the true facts come above board to the world.”
Reporter: “Are these people in very high positions Jack?”
Jack: “Yes.”

http://richardcharnin.com/

Richard Charnin
Feb.5, 2013

A matrix is a rectangular array of numbers. The 1968-2012 National True Vote Model (TVM) is an application based on Matrix Algebra. The key to understanding the theory is mathematical subscript notation. The actual mathematics is really nothing more than simple arithmetic.

The model is easy to use. Just two inputs are required: the election year and calculation method (1-5). Each method uses the final adjusted National Exit Poll vote shares, but methods 2-5 change the returning voter mix to a feasible one (calculation method):
Method 1 displays the adjusted National Exit Poll which is always forced to match the recorded vote.
Method 2 assumes returning voters based on the previous election recorded vote.
Method 3 assumes returning voters based on the previous election votes cast (allocates uncounted votes).
Method 4 assumes returning voters based on the previous election unadjusted national exit poll.
Method 5 calculates the True Vote based on the previous election True Vote.

The True Vote (TV) is a function of the number of previous election returning and new voters in the current election and each candidate’s share of these voters.
TV = f(turnout, vote shares)

The US Vote Census estimates the number of votes cast in each election. Total votes cast include uncounted ballots, as opposed to the official recorded vote.

The True Vote Model is based on total votes cast – as it should be. There were approximately 40 million uncounted votes in the 6 elections from 1988-2008. Uncounted ballots are strongly Democratic.

Let TVP = total votes cast in previous election
Let TVC = total votes cast in the current election

The number of returning voters (RV) is estimated based on previous election voter mortality (5%) and an estimated turnout rate (TR).

For example, in 2004 there was an estimated 98% turnout (TR) of living 2000 voters. Voter mortality (VM) is 5% over four years (1.25% per year). We calculate returning 2000 voters as:
RV = TVP * (1- VM) * TR
RV = 103.2 = 110.8 * .95 * .98

There were 125.7 million votes cast in 2004. Therefore, we calculate the number of new voters TVN as:
TVN = TVC – RV
TVN = 24.5 = 125.7 – 103.2

In the base case we assume an equal turnout rate of previous election Democratic, Republican and other (third-party) voters.
V (1) = returning Democratic voters
V (2) = returning Republican voters
V (3) = returning other (third-party) voters
RV = V (1) + V (2) + V (3) = total returning voters
V (4) = TVC – RV = number of new voters.

Calculate m (i) as the percentage mix of total votes cast (TVC) for returning and new voters V(i):
m (i) = V (i) / TVC, i=1, 4

Let a (i, j) = candidates (j=1,3) vote shares of returning and new voters (i=1,4).

True Vote calculation matrix
Vote Mix Dem Rep Other
Dem m1 a11 a12 a13
Rep m2 a21 a22 a23
Oth m3 a31 a32 a33
Dnv m4 a41 a42 a43

The total Democratic share is:
VS(1) = ∑ m(i) * a(i, 1), i=1,4
This is mathematical notation for the sum of the products:
VS(1)= m(1) * a(1,1) + m(2) * a(2,1) + m(3) * a(3,1) + m(4) * a(4,1)

Republican share: VS(2) = ∑ m(i) * a(i,2), i=1,4
Third-party share:VS(3) = ∑ m(i) * a(i,3), i=1,4

Mathematical vote share constraints
Returning and new voter Mix sum to 100%
∑m (i) =100%, i= 1, 4

Candidate shares of returning and new voters sum to 100%
∑a (1, j) =100%, j=1, 3
∑a (2, j) =100%, j=1, 3
∑a (3, j) =100%, j=1, 3
∑a (4, j) =100%, j=1, 3

Total (Democratic+ Republican + Other) vote shares sum to 100%
∑ VS (i) = 100%, i=1,3

Adjusted Exit Poll: Matrix of Deceit
It is obvious that there must be fewer returning voters than voted in the prior election for each of the Democrat, Republican and third-party candidates. Approximately 5% die in the four years between elections.

But according to the adjusted, published National Exit Poll, there were millions more returning Bush voters from the previous election than were living in 1988, 1992, 2004 and 2008 – a mathematical impossibility and proof of election fraud beyond any doubt.

Sensitivity Matrix: alternative scenarios
These tables gauge the sensitivity of the total candidate vote shares to changes in their shares of returning and new voters.

In 2004,Bush won the recorded vote by 3 million (50.7-48.3%). However, at the 12:22am National Exit Poll timeline (13047 respondents), Kerry had 91% of returning Gore voters, 10% of returning Bush voters and 57% of New voters. In this base case scenario, Kerry had a 53.6% True Vote share and 10.7 million vote margin.

Adjusting the base case vote shares to view worst case scenarios:
1) Kerry has 91% (no change) of returning Gore voters, just 8% of returning Bush voters and 53% of New voters. Kerry’s total vote share is reduced to 52.1% and a 7.2 million winning margin.

2) Kerry has just 89% of returning Gore voters, 8% of returning Bush voters and 57% of New voters (no change). Kerry’s total vote share is reduced to 52.0% and a 6.9 million margin.

3) Assume the base case vote shares, but change the 98% returning 2000 voter turnout rate to 94% for Gore and 100% for Bush. Kerry’s total vote share is reduced to 52.7% and a 8.5 million margin.

4) Assume the base case 98% turnout of returning Gore and Bush voters and 91% Kerry share of returning Gore voters. To match the fraudulent recorded vote, Bush needed 61% of New voters compared to his 41% exit poll share. He also needed 96% of returning Bush voters compared to his 90% exit poll share. Both shares far exceeded the 2% margin of error. The probabilities are infinitesimal.

The sensitivity analysis confirms that the election was stolen. Kerry won all plausible (and implausible) scenarios. Bush needed an impossible 110% turnout of Bush 2000 voters to win the fraudulent recorded vote.

Adjusted 2004 National Exit Poll (match recorded vote)
2000 Votes Mix Kerry Bush Other Turnout
Gore 45.25 37% 90% 10% 0.0% 93.4%
Bush 52.59 43. 9.0 91. 0.0 109.7 (impossible)
Other 3.67 3.0 64. 14. 22. 97.7
DNV. 20.79 17. 54. 44. 2.0 -

http://richardcharnin.com/

Historical Overview

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

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

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

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

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

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

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

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

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

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

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

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

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

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

In July 2004 I began posting weekly Election Model projections based on the state and national polls. The model was the first to use Monte Carlo Simulation and sensitivity analysis to calculate the probability of winning the electoral vote. The final projection had Kerry winning 337 electoral votes and 51.8% of the two-party vote, closely matching the unadjusted exit polls.

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

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

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

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

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

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

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

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

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

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

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

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

http://richardcharnin.com/

Richard Charnin
Jan. 22,2013

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

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

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

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

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

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

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

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

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

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

Sensitivity Analysis

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

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

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

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

Richard Charnin
Jan. 19, 2013

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

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

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

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

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

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

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

2010 Midterms Overview
True Vote Model Analysis

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

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

Richard Charnin
Jan. 14, 2013

In previous posts, we have noted the dramatic 7% difference between Obama’s Election Day and late recorded vote share in both 2008 and 2012. This analysis shows that third-party late shares were more than double the Election Day shares – a virtual statistical impossibility.

In 2008, there were 121.21 million votes recorded on Election Day; Obama led by 52.34-46.31% (1.35% to third-parties). There were 10.16 million late votes; Obama led by 59.16-37.48% (3.36% to third-parties).

In 2012, there were 117.46 million votes recorded on Election Day; Obama led by 50.34-48.07% (1.59% to third-parties). There were 11.68 million late votes; Obama led by 57.99-38.29% (3.72% to third-parties).

Are late votes representative of the electorate as a whole? One check is to weight (multiply) the late state vote shares by the total state vote.

2008 Weighted Late Vote Shares:
Obama 57.4- McCain 38.6- Other 4.0%
The third-party late share is within 0.6% of the 3.36% recorded late share.
Obama had 58.0% in the state exit poll aggregate and the True Vote Model (within 0.6% of his weighted late share).

2012 Weighted Late Vote Shares:
Obama 54.0- Romney 41.8- Other 4.2%
The third-party late share is within 0.5% of the 3.7% recorded late share.
Obama had 56.1% in the 2-party True Vote Model (within 0.3% of his weighted 2-party late share). Only 31 states were exit polled in 2012. Unadjusted polling data is unavailable.

So what do the third-party numbers indicate? Consider that:
- Obama’s 2008 late vote shares closely match the 2008 state exit polls (within 1%).
- Obama’s 2008 and 2012 late vote shares closely match the True Vote Models (within 1%).

Third-party 2008 and 2012 late state vote shares
- closely match the late recorded shares (within 0.5%).
- were more than double the Election Day shares.

Therefore, since the Obama and third party weighted late shares were a close match to the late recorded shares, it is likely that the increase in the third party late share over the Election Day share was caused by a combination of a) vote flipping on Election Day from third parties to McCain and Romney, b) higher third party provisional and absentee voting rates, c) discarding of absentee and provisional Obama ballots which increased third-party late vote shares.

If 50% of the difference in third party late vote shares and Election Day shares was due to vote flipping, then approximately one million (1%) of the votes recorded on Election Day were flipped from the third-parties to McCain and Romney.

Election Day and Late Vote shares
(weighted by total state vote)
2008
Obama McCain Other Calculated
52.87% 45.62% 1.51% Total Votes
52.34% 46.31% 1.35% Election Day
52.25% 46.51% 1.24% Election Day Weighted
59.15% 37.47% 3.34% Late Recorded
55.80% 40.90% 3.30% Late Weighted
58.00% 40.30% 1.70% Exit Poll & True Vote Model

Calculated Share........5,581 100.00% 50.67% 47.86% 1.47% 2.81%
Recorded Share........................50.67% 47.86% 1.47% 2.81%
True Share............................53.97% 44.56% 1.47% 9.42%


Track Record: Election Model Forecast; Post-election True Vote Model

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

2006 Midterms: Regression Generic Poll Trend Model
Projected Democratic share: 56.43%
Unadjusted National Exit Poll: 56.37%

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

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