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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.

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.


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

JFK Calc:

1988-2008 Unadjusted Exit Polls:

1988-2012 State and National True Vote Model:

1968-2012 National True Vote Model:

2012 True Vote Model:

2004 Election Monte Carlo Forecast and Exit Poll Simulation:

2004 County Presidential True Vote:

Walker Recall:

Walker Recall: County/Muni True Vote:

Walker Recall Cumulative Vote Shares:

Wisconsin True Vote: Supreme Court, State Senate Recalls, 2010 Senate:

2008 WI Presidential Cumulative Vote Shares:

Latin American Leader Cancer:

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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.

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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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Executive Action: JFK Witness Deaths and the London Times Actuary

Executive Action: JFK Witness Deaths and the London Times Actuary

Richard Charnin
Feb. 25, 2013
Updated: June 11, 2014

JFK Blog Posts
JFK Calc Spreadsheet Database

The 1973 film Executive Action depicted a conspiracy to assassinate JFK. Burt Lancaster and Robert Ryan, who played CIA operatives involved in the plot, 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.

“In the three-year period which followed the murder of President Kennedy and Lee Harvey Oswald, 18 material witnesses died – six by gunfire, three in motor accidents, two by suicide, one from a cut throat, one from a karate chop to the neck, three from heart attacks and two from natural causes”.

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.

The London Sunday Times
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 legal manager did not provide the House Select Committee on Assassinations (HSCA) the actuary’s calculation assumptions or methodology. He claimed that the problem was not clearly defined. The HSCA compounded the obfuscation when their statistician claimed that the witness universe was unknowable and therefore the calculation was not valid.

In a response to a letter from the HSCA in 1977, 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. No one on the editorial staff remembered his name? Really? And we are supposed to believe that? Only the actuary could explain his interpretation of the problem and method of calculation. Those statements made no sense; nothing else the Times legal manager 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 interval 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. Unnatural death mortality statistics and probability calculations used by the actuary were not provided to the HSCA. Was it because they would show that the calculation was plausible and essentially correct?

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. Even if the Times editor did not specify unnatural deaths, it does not follow that the actuary was oblivious to the distinction.

In fact, the actuary’s calculation was confirmed assuming 552 witnesses, the number who testified at the Warren Commission. Is it just a coincidence that at least 30 Warren Commission witnesses (listed in the JFK Calc database with links to their testimony) died unnaturally and/or suspiciously or that scores of others died mysteriously at convenient times just before they were due to give testimony at the Garrison/Shaw trial, Church hearings and HSCA?

It is important to re-emphasize that Whitaker said not a word about unnatural deaths. 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. The HSCA claim that the odds were impossible to calculate was a ruse like the Single Bullet Theory (SBT).

The 552 Warren Commission witnesses IS a KNOWN UNIVERSE. At least 30 died suspiciously from 1964-78. Fourteen (14) deaths were RULED to be unnatural: 4 homicides, 6 accidents and 4 suicides. Just one or two would normally have been expected based on UNNATURAL MORTALITY RATES.. The probability of 14 RULED UNNATURAL deaths is 7E-07 (1 in 1.4 MILLION). But the 10 “suicides” and “accidents” were LIKELY homicides. The probability of 14 HOMICIDES is 3.9E-14 (1 in 25 TRILLION).

The 552 Warren Commission witnesses IS 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 mathematical proof of conspiracy based on factual data: 552 Warren Commission witnesses, at least 20 unnatural deaths, published mortality rates and use of the Poisson probability function. The numbers and probabilities speak for themselves. This is a sensitivity analysis of unnatural witness deaths.

Hess conveniently left out scores of mysterious, unnatural deaths in her list of 21 witnesses. She noted five that were questionable. But even the “natural” deaths were suspicious. For example, Jack Ruby died just before his second trial, 29 days after being diagnosed with cancer. He claimed that he was injected with a virus. Thomas Howard, Ruby’s lawyer, died of a heart attack at age 53 in March 1965. There was no autopsy. Howard met with two reporters, Jim Koethe and Bill Hunter, in Ruby’s apartment on Nov. 24, 1963. The reporters were murdered. All three died within 16 months of the meeting.

Hess did not include David Ferrie and Eladio del Valle. David Ferrie 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. Ferrie associate del Valle was also sought by Garrison. He was murdered on Feb. 21, the same day as Ferrie.

Hess neglected every one of the 20 deaths of prospective HSCA witnesses! She gave a convoluted excuse in response to a question as to why she did not include George De Morenschildt, Oswald’s close friend (and intelligence operative) who allegedly shot himself the day he was notified that he was to be interviewed 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 as mentioned above, even her list of 21 witnesses in the 1964-1967 period did not include at least 25 others.

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” otherwise she would have done the calculations herself.

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 the 50-year old myth is still presented as gospel by the mainstream media and overwhelming scientific ballistic, acoustic, video, medical, eyewitness and mathematical evidence of suspicious deaths is ignored.

The HSCA noted just 21 witness deaths.

These tables and graphs prove a conspiracy beyond any doubt:

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%.

But there are two major problems with Musen’s calculation.
1- The index includes names of individuals who had no connection whatsoever to the assassination, such as George Washington and many others. Only 552 witnesses testified in person or by deposition.

2- Musen did not consider unnatural deaths. Even assuming an inflated 2479 witnesses, approximately 7 unnatural deaths would be expected over a three year period.

So how did the actuary calculate the probability? If he/she assumed 459 witnesses, then given 18 deaths (8 homicides, 3 accidents, 2 suicides, 3 heart attacks, 2 natural causes) and the 0.000207 total weighted mortality rate, the probability is 9.96E-18 or 1 in 100,000 trillion.

In fact, there were at least 47 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 that at least 42 of the 47 deaths were unnatural (homicide, accident, suicide, unknown).

Using the .000831 unweighted unnatural death rate, the odds that at least 47 would die unnaturally within 3 years is E-25 or 1 in 10 trillion trillion.

The JFK Calc spreadsheet database consists of 122 material witnesses who died unnaturally or suspiciously from 1964-78. Researchers claim there were many more. Of the 122, 78 were officially ruled unnatural (34 homicides, 24 accidents, 16 suicides, 4 unknown). The other deaths were a combination of suspicious heart attacks, sudden cancers and unknown causes.

But a statistical analysis of expected deaths for various causes indicates there were actually close to 90 homicides (the number of officially ruled deaths by accident, suicide and heart attack far exceeded the expectation).

The probability of 34 OFFICIAL RULED HOMICIDES among 1400 JFK-related individuals from 1964-78 is 1.57E-31 =1/ 6 million trillion trillion using the average 0.000084 homicide rate.

P= E-62= 1/trillion^5 = ZERO using the JFK-weighted average unnatural rate.
P= E-27= 1/trillion^2 = ZERO using the unweighted national average unnatural rate.

Another way of looking at it is to ask how many unnatural deaths were required in the 15 year period (assuming 1400 material witnesses) to obtain a probability of less than 1% (beyond a reasonable doubt). The answer is 30. As the number of deaths increase, the probability rapidly approaches ZERO. But there were over 80.

In 1964-78, there were at least 67 deaths of approximately 1100 material witnesses who were called to testify at the Warren Commission, Clay Shaw trial, Church Senate Committee and the House Select Committee on Assassinations (HSCA). Given that 28 deaths were homicides, the probability is 2.3E-26 (1 in 40 TRILLION TRILLION).

Warren Commission apologists have suggested that there were 25,000 witnesses interviewed without providing a list. How many were material? Only about 1400. But even assuming 25,000, the probability of at least 26 homicides in three years is 1 in 490 BILLION. So much for the bogus 25,000 witnesses argument.

This is a challenge to those who still claim that the deaths do not prove a conspiracy: To substantiate that claim, they must refute the data (i.e., the Warren Commission witness list), the unnatural mortality rates and the use of the Poisson formula.

Source: U.S. National Center for Health Statistics

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) 121 eyewitnesses who gave depositions to the FBI (51 said the shots came from the area of the Grassy Knoll, 32 from the Texas Book Depository, 38 were unsure), 2) witnesses called by the 1964 Warren Commission, 3) Jim Garrison/Clay Shaw trial, 4) Senate Intelligence (Church) Committee, 5) House Select Committee (HSCA) and 6) 1400+ JFK-related witnesses.

The timings of the deaths make it all the more suspicious. At least 22 died within one year of the assassination (Warren Commission). At least 16 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 of 50 deaths by Richard Belzer and David Wayne (published April 2013).

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. A plausible universe of 1400+ JFK-related witnesses is presented in the Who’s Who in the Kennedy Assassination reference.

Mark Lane debunked the Warren Commission in his book and film: Rush to Judgment.

The Poisson Probability Distribution

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.

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 average 1964-78 unnatural death rate R is approximately 0.000822.

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

Key witness categories
1 Unnatural deaths vs. suspicious natural deaths 1964-78
2 Investigation witnesses sought: Warren, Garrison, Church, HSCA (1100 est)
3 Investigation witnesses who died in 1964-78 (67)
4 Approximate number of JFK-related witnesses (1400+)
5 Eyewitnesses (121)

- The unnatural death rate is used in the analysis.
– ZERO probability of unnatural deaths in all categories.
– 51 Warren Commission eyewitnesses claimed that the shots came from the Grassy Knoll, 32 from the Texas Schoolbook Depository and 38 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.
– Bill Hunter, a reporter, shot by a policeman in April 1964 – 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.
The probability of the three deaths in one year: 1 in 300 million!

7 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).
. William Sullivan- Head of counter/espionage. Predicted death. Hunting accident.
. James Cadigan- Document expert; previously testified to WC. Accidental fall.
. Regis Kennedy- Heart attack the day he was to testify.
. 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

Jack Ruby died in Jan, 1967, just 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.
“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?”
Ruby: “Yes.”

In Feb. 1967, David Ferrie was found dead in his apartment shortly after he was named as a defendant by New Orleans D.A. Jim Garrison in the Clay Shaw trial. 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.

Guy Banister, an ex-FBI agent with ties to Ferrie and Oswald, died in 1964, supposedly from a heart attack.

Maurice Gatlin was also sought by Garrison. He 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.

Clay Shaw denied he was CIA and was acquitted. He died a few years later from sudden cancer. There was no autopsy. CIA Director Richard Helms later admitted under oath that Shaw was a CIA contractor.

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.

There were at least 122 suspicious deaths among an estimated 1400 JFK material witnesses. At least 78 were ruled unnatural: 34 homicides, 24 accidents, 16 suicides, 4 unknown. Given the 1964-1978 national average unnatural mortality rate, 17 unnatural deaths would be expected. The probability of 78 unnatural deaths is ZERO But how many “accidents”, “suicides” and suspicious “natural” deaths were actually homicides? The probabilities would be lower still.

The reference Who’s Who in the JFK Assassination describes approximately 1400 individuals who were related in any way to the assassination; 95 are included in JFK Calc (70 were unnatural deaths). But the other 23 witnesses that are not included in Who’s Who are very relevant.

It is important to note that the 1964-78 average homicide rate (1 in 12,000) was much lower than accidental deaths (1 in 1,600) and suicides (1 in 7,700). An analysis comparing unnatural JFK witness deaths to the expected number is not nearly as dramatic as comparing homicides. Nationally, homicides comprised 10% of unnatural deaths. But there were 34 ruled homicides among the 78 unnatural deaths (44%). If the analysis was restricted to homicides, the mathematical proof would be simpler and more powerful.

Unnatural Official Deaths; National Average Rates (1964-78)
Homicide (34): 0.000084 (1 in 12,000)
Accident (24): 0.000594 (1 in 1,600)
Suicide (16): 0.000130 (1 in 7,700)
Unknown (4): 0.000014 (1 in 100,000)
Total (78): 0.000822 (1 in 1,200)

Natural Death Rates
Heart Disease (25): 0.004913 (1 in 200)
Cancer: (6) 0.001991 (1 in 500)
Other: (13) 0.004461 (1 in 1000)
Total (44): 0.010197 (1 in 100)


Posted by on February 25, 2013 in JFK, 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.

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

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

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.

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

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

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.

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%
56.0% 5.7 10.2 16.2
55.0% 4.9 9.4 15.4
49.0% 0.0 4.5 10.5


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


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.

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.

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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