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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

Recent Interviews
Bob Fitrakis:
Jack Duffy:
Jim Fetzer:

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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JFK Witness Deaths: Graphical Proof of a Conspiracy

JFK Witness Deaths: Graphical Proof of a Conspiracy

Richard Charnin
Oct.14, 2013
Updated:Dec.20, 2013

JFK Blog Posts
JFK Calc Spreadsheet Database
Probability Tables

This post is updated for the latest data, analysis and graphics from the JFK Calc Spreadsheet/database of Unnatural and Suspicious Deaths. Mortality rates used for expected deaths and probabilities are from

Assuming that 1400+ material witnesses were connected to the assassination, then based on annual mortality rates for major causes of death, 214 deaths were expected in the 1964-78 period (196 natural and 18 unnatural). But there were at least 96 unnatural deaths (80 homicides, 5 suicides, 8 accidents, 3 unknown).

The Poisson distribution function calculates the probability of rare events based on two factors: the actual (n) and expected number E. Given N=1400 witnesses, T=15 years, n=96 unnatural deaths, R=0.000127 (JFK-weighted mortality):
E = 2.66 = 1400*15*0.000127
P = Poisson (96, 2.66, false) = 3.26E-111
P = E-61 for 78 official unnatural deaths (1 in a trillion trillion trillion trillion trillion).

There are 120 suspicious deaths listed in JFK Calc. Seventy-seven (77) were officially ruled to be unnatural (34 homicides, 16 suicides, 24 accidents, 3 unknown). Forty-two (42) were ruled natural (heart attacks, cancers, other). But since many accidents, suicides and natural deaths were likely homicides, the number of unnatural deaths was adjusted to 96 (including 80 homicides).

To put the magnitude of the probabilities in context, there are approximately 10^24 (one trillion trillion) stars in the universe. The virtual ZERO probability of guessing the name of a star is much higher than the probability that there was not a conspiracy to assassinate JFK. This is mathematical proof of a conspiracy beyond any doubt.

The 1964-78 national homicide rate was 0.000084 (8 per 100,000). Therefore, among an estimated 1400+ JFK-related witnesses, only two (1400*15*.000084) homicides would normally be expected in the 15 year period. But there were at least 80 homicides. It is conceivable that among the other 40 deaths, as many as 20 were actually homicides and therefore 100 of 1400+ material witnesses were murdered. Only 17 natural and one unnatural death would normally be expected in a group of 120 in 15 years.

These books are highly recommended for detailed information on JFK witnesses:
Who’s Who in the JFK Assassination by Michael Benson (1400+ names, 95 in JFK Calc)
Hit List by Richard Belzer and David Wayne (50 suspicious deaths, all in JFK Calc)
Crossfire by Jim Marrs (103 “convenient” deaths, virtually all in JFK Calc)
They Killed Our President by Jesse Ventura, Richard Russell and David Wayne (63 reasons)

Expected Deaths (1964-78)
1400 material witnesses
(based on annual mortality rates)
Natural. 196 14.02%
Unnatural 18 1.25%
Total… 214 15.28%

JFK Calc: 120 witness deaths (expected vs. actual)
Cause of Death, (Exp)ected (Off)icial (JFK)Calc (average 1964-78 mortality rate)
Cause..........Exp Off JFK Rate
Homicide...... 0.15 34 80 (0.000084)
Accident...... 1.00 24 08 (0.000594)
Suicide....... 0.23 16 05 (0.000130)
Unknown........0.02 03 03 (0.000010)
Total...........1.4 77 96 (0.000818)

Cardiac........ 8.7 22 12 (0.004913)
Cancer......... 3.5 06 05 (0.001991)
Other.......... 4.6 14 07 (0.002480)
Total..........16.8 42 24 (0.009375)

ALL DEATHS.....18.2 120 120 (0.010193)

.... Begin Card Canc Vasc Oth Accid Suic Homic End
1964 1,400 7.61 2.71 2.39 1.26 0.90 0.18 0.08 1,385
1965 1,385 7.60 2.74 2.37 1.25 0.90 0.18 0.08 1,370
1966 1,370 7.58 2.75 2.36 1.25 0.92 0.18 0.08 1,355
1967 1,355 7.35 2.76 2.33 1.24 0.92 0.18 0.09 1,340
1968 1,340 7.43 2.78 2.32 1.26 0.92 0.18 0.09 1,325
1969 1,325 7.24 2.78 2.30 1.27 0.92 0.18 0.10 1,310
1970 1,310 6.90 2.78 2.27 1.27 0.91 0.18 0.10 1,296
1971 1,296 6.90 2.79 2.25 1.26 0.90 0.18 0.10 1,281
1972 1,281 6.86 2.80 2.23 1.25 0.90 0.18 0.11 1,267
1973 1,267 6.75 2.80 2.21 1.25 0.89 0.18 0.11 1,253
1974 1,253 6.42 2.82 2.19 1.24 0.88 0.18 0.11 1,239
1975 1,239 6.04 2.80 2.15 1.23 0.87 0.18 0.12 1,225
1976 1,225 5.98 2.84 2.12 1.22 0.85 0.18 0.12 1,212
1977 1,212 5.79 2.85 2.08 1.21 0.84 0.18 0.12 1,199
1978 1,199 5.74 2.87 2.04 1.20 0.83 0.18 0.12 1,186
....Total...102.. 42.. 34.. 19.. 13.. 3.. 2.. 214
....Share.. 7.3% 3.0% 2.4% 1.3% 0.9% 0.2% 0.1% 15.3%

1- Deaths spiked in 1964 (Warren Commission) and 1977 (House Select Committee).

2. 63 of 120 witnesses in JFK Calc were sought in four investigations.

3. Unnatural deaths far exceeded expected based on national mortality rates.

4. The probability of 33 unnatural deaths among 1400 witnesses is ZERO.

5. Sensitivity analysis probabilities:10-50 unnatural deaths; 1500-2500 witnesses.

6. Even assuming 25,000 FBI interviews, the probability of at least 38 homicides in 1964-66 is E-23. Only 4-5 would normally be expected.

7. There were at least 20 unnatural deaths (17 homicides) of 552 Warren Commission witnesses from 1964-78. Only 7 would normally be expected.

8. There were at least 42 homicides of 1100 witnesses sought in 4 investigations. Only one was expected.

9. ZERO probability of 15 unnatural deaths in 7 years and 30 deaths in 15 years.

10. Given 1400 JFK-related witnesses and average 1964-78 U.S. unnatural mortality rates, the ZERO probability threshold is 30 deaths. The unweighted probability of 96 unnatural deaths is E-39. The JFK-weighted probability is E-111.

11. Estimated Expected (214) and Actual (291) deaths of 1400 JFK-related individuals (1964-78) ; 120 listed in JFK Calc

12. About 50 of the 120 deaths were in Dallas which has a higher mortality rate than the national average. I tripled the national homicide rate from 0.000084 to 0.000253.
The probability P of 34 official homicides using the adjusted Dallas rate is P = 7.60e-17 or 1 in 13,000 trillion.


Sample Probabilities

At least 18 deaths (13 unnatural); assume 459 witnesses

Normally, 2 unnatural deaths would be expected.
Using the 0.000207 weighted rate, the probability is ZERO.
P = E-17 = POISSON (13, .29, true)
P = 1 in 100,000 trillion

WARREN COMMISSION- 552 witnesses
At least 21 unnatural deaths among 552 witnesses

Normally, 7 unnatural deaths would be expected from 1964-78.
Using the 0.000135 weighted WC witness rate, the probability of at least 21 unnatural deaths is ZERO:
P = E-20 = POISSON (21, 1.12, false)
P = 1 in 15 million trillion

Probability of 18 homicides is ZERO:
P = E-19 = POISSON(18, 0.53, true)
P = 1 in 8 million trillion

1400 MATERIAL WITNESSES (Who's Who in the JFK Assassination)
1964-66: at least 45 unnatural deaths

Normally, 3 would be expected.
Using the 0.000842 unweighted national rate, the probability is ZERO:
P = E-33 = POISSON (45, 3.53, false)
P = 1 in 10 million trillion trillion

1964-78: at least 96 unnatural deaths
Normally, 17 would be expected.
Using the 0.000818 unweighted national rate, the probability is ZERO:
P = E-39 = POISSON (96, 17.18, false)
P = 1 in 1000 trillion trillion trillion

Using the JFK-weighted rate (0.000127):
P = E-111 = POISSON (96, 2.66, false)

1964-78: at least 80 homicides
Normally, 2 would be expected.
Using the 0.000084 average national homicide rate, the probability is ZERO:
P = E-100 = POISSON (80, 1.77, false)

Four Investigations: 1100+ witnesses called or sought to testify
49 unnatural deaths (14 expected).
Using the 0.000106 unnatural weighted rate, the probability is ZERO:
P = E-51 = POISSON (49, 1.81, false)

1964-78: 25,000 FBI Interviews
At least 80 homicides (32 expected)
Using the 0.000084 average national homicide rate, the probability is ZERO:
P = E-23 = POISSON (80, 31.62, false)
P= 1 in 2 trillion


Witnesses: N
Homicides: n
Time: T= 15 years
Rate: R= 0.000084
Prob: P= POISSON(n, N*R*T, false)

Example: In the table, the probability P of n=50 homicides among N=1400 JFK-related individuals over the T=15 years from 1964-78 is P= 1.42E-53 = 0.0000000000 0000000000 0000000000 0000000000 0000000000 001

The probability is of course higher assuming N=8000 JFK-related individuals: P= 2.38E-19 (1 in 4 million trillion). Ten (8000*15*0.000084) homicides would normally be expected.

........................................Homicides (n) .........................
N......10...... 20...... 30...... 40...... 50...... 60...... 70...... 80
Warren Commission
552 3.77E-09 1.55E-22 3.90E-38 3.48E-55 2.57E-73 2.58E-92 4.93E-112 2.27E-132

4 Investigations
1100 1.86E-06 7.54E-17 1.88E-29 1.66E-43 1.21E-58 1.20E-74 2.26E-91 1.03E-108

"Who's Who in the JFK Assassination"
1400 1.42E-05 6.41E-15 1.78E-26 1.75E-39 1.42E-53 1.58E-68 3.31E-84 1.68E-100

Warren Commission Index
2479 1.10E-03 1.50E-10 1.27E-19 3.78E-30 9.30E-42 3.12E-54 1.99E-67 3.05E-81

3000 3.83E-03 3.53E-09 2.00E-17 4.03E-27 6.67E-38 1.51E-49 6.47E-62 6.70E-75
4000 1.92E-02 3.15E-07 3.17E-14 1.13E-22 3.33E-32 1.33E-42 1.02E-53 1.87E-65

5000 5.05E-02 7.70E-06 7.22E-12 2.40E-19 6.58E-28 2.46E-37 1.75E-47 2.99E-58
6000 8.83E-02 8.34E-05 4.84E-10 9.96E-17 1.69E-24 3.91E-33 1.72E-42 1.82E-52

7000 1.16E-01 5.14E-04 1.39E-08 1.34E-14 1.06E-21 1.15E-29 2.36E-38 1.17E-47
8000 1.25E-01 2.10E-03 2.16E-07 7.89E-13 2.38E-19 9.78E-27 7.63E-35 1.44E-43


Posted by on October 14, 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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Hit List: An In-Depth Investigation into the Mysterious Deaths of Witnesses to the JFK Assassination

Richard Charnin
April 18, 2013
Updated Nov.5, 2013

JFK Blog Posts
JFK Calc Spreadsheet Database

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.

Here are the graphs and probability calculations which prove a conspiracy:

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.

The actuary’s odds are confirmed assuming:459 witnesses and 0.000207 weighted total mortality rate.

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 18 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 is a sensitivity analysis of unnatural witness deaths.

There were approximately 1400 JFK-related witnesses. In 1964-1978, at least 83 died unnaturally (homicide, suicide, accidental, unknown) and 35 deaths were suspiciously timed heart attacks, cancers, etc. Normally 17 unnatural deaths would be expected.

Some have questioned the relevance of the unnatural and suspicious witness deaths related to the assassination. Of the 118 witnesses in the spreadsheet database, 30 testified at the Warren Commission, 32 were sought or testified at the Clay Shaw trial by prosecutor Jim Garrison, the Church Senate Committee, and the House Select Committee on Assassinations (HSCA). Thirteen testified or were sought in two of the investigations. Therefore, at least 62 of the 118 witnesses in the database are indisputably relevant. What are the odds that 38 witnesses called to testify in the four investigations would meet unnatural deaths?
Less than 1 in a 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)

Given: average 1964-78 unnatural mortality rate of 0.000808 the probability of
at least 18 UNNATURAL deaths within ONE year of the assassination is E-16 (1 in 1200 TRILLION).
42 UNNATURAL deaths within THREE years of the assassination is ZERO.
83 UNNATURAL deaths within FIFTEEN years of the assassination is ZERO.

Assuming the JFK witness WEIGHTED unnatural rate, the probability of
at least 18 UNNATURAL deaths among 552 Warren Commission witnesses is 1 in 60 BILLION
37 UNNATURAL deaths among 1100+ witnesses called by WC, Garrison, Senate, HSCA is ZERO.
83 UNNATURAL deaths among 1400+ material witnesses is ZERO (E-70)

The average national UNNATURAL rate in 1964-78 was 0.000818.
The average national HOMICIDE rate in 1964-66 was 0.000059.
There were at least 24 homicides in 3 years. P = less than 1 in a trillion trillion trillion)
The average national HOMICIDE rate in 1964-78 was 0.000084.
There were at least 49 homicides in 15 years (Prob. less than 1 in a 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. Even assuming 25,000 witnesses, then given the 0.000084 homicide rate, the probability is 1 in 12 billion of 24 homicides in the 3 years following the assassination. But how many of the 23 suicides, accidents, heart attacks and sudden cancers were actually homicides? The probability would be much lower. So much for the bogus 25,000 witnesses argument.

This graph shows the long-term trend in U.S. homicide rate. Note that in 1963 the rate was approximately 6 per 100,000. The average rate from 1964-78 was 0.000084.

Warren Commission – 552 witnesses
In the 3 years following the assassination, there were at least 10 unnatural deaths. Applying the 0.000245 weighted unnatural rate, the probability is 1 in 44 BILLION.

There were at least 18 unnatural deaths from 1964-78. Applying the 0.000257 weighted unnatural mortality rate, the probability is 1 in 60 BILLION. There were 11 HOMICIDES. Using the 0.000084 homicide rate, the probability is 1 in 4 BILLION.

The following unnatural mortality rate table displays the cause of death, expected number of deaths among 1400 witnesses, actual number of deaths,mortality rate, and JFK witness vs. U.S. unnatural death weightings.

Cause.......... Exp Actual Rate JFK U.S.
Homicide....... 1.77 49 0.000084 57% 10%
Suicide........ 2.73 07 0.000130 10% 16%
Accident.......12.47 23 0.000594 29% 73%
Unknown........ 0.21 03 0.000010 04% 01%
Total..........17.18 83 0.000818 100% 100%
JFK weighted... 4.93 83 0.000235 -

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Posted by on April 18, 2013 in JFK, 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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The True Vote Model: A Mathematical Formulation

The True Vote Model: A Mathematical Formulation

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). The calculation methods are:
1- National Exit Poll (“mix” adjusted to match the recorded vote)
Returning voter turnout calculated based on the previous election
2- recorded vote
3- votes cast (including allocated uncounted votes)
4- unadjusted national exit poll
5- True Vote

In each election, the Final National Exit Poll vote shares are used – except for 2004 in which 12:22am shares are used; they were “adjusted” and forced to match the recorded vote.

Matrix of Deceit

According to the adjusted 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.

It is obvious that there must be fewer returning voters than the number who voted in the prior election for each candidate. Approximately 5% of voters pass in the four years between elections.

The US Vote Census provides an estimate of the number of votes cast in each election. Total votes cast include uncounted ballots, as opposed to the official recorded vote. There were approximately 40 million uncounted votes in the 6 elections from 1988-2008. Uncounted ballots are strongly Democratic.

The National True Vote Model is based on total votes cast in the prior and current election. The True Vote (TV) is a function of the number of previous election returning and new voters and each candidate’s share of these voters.

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.

Sensitivity analysis indicates that Kerry won all plausible (and implausible) scenarios. Bush needed an impossible 110% turnout of Bush 2000 voters to win the fraudulent recorded vote.

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. The required shares easily exceeded the 2% margin of error. The probabilities are infinitesimal.

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

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

In 2000, 110.8 million votes (TVP) were cast. Voter mortality (VM) is 5% over four years. In the base case, we assume equal 98% turnout (TR) of living 2000 voters. We calculate (RV) returning 2000 voters:
RV = TVP * (1- VM) * TR
RV = 103.2 = 110.8 * .95 * .98

In 2004, 125.7 million votes were cast. The number of new 2004 voters (TVN) is the difference between 2004 votes cast (TVC) and returning 2000 voters (RV):
TVN = 24.5 = 125.7 – 103.2

Matrix notation
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 a shortcut mathematical notation for:
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 percentages must total 100%.
∑m (i) =100%, i= 1, 4

Candidate shares of returning and new voters must total 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

Democratic + Republican + third-party vote shares must total 100%.
∑ VS (i) = 100%, i=1,3

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 -
Total 122.3 100% 48.3% 50.7% 1.0% 101.4%

2004 True Vote Model
2000 Votes Mix Kerry Bush Other Turnout
Gore 52.13 41.5% 91% 9.0% 0% 98%
Bush 47.36 37.7 10.0 90.0 0.0 98
Other 3.82 3.00 64.0 14.0 22. 98
DNV. 22.42 17.8 57.0 41.0 2.0 -
Total 125.7 100% 53.5% 45.4% 1.0% 98%

Kerry share of New voters (DNV)
Pct 39.% 55.% 57.% 59.% 61.%
of Bush........ Kerry % Vote Share
12% 51.1 54.0 54.3 54.7 55.1
11% 50.7 53.6 54.0 54.3 54.7
10% 50.4 53.2 53.6 53.9 54.3
9.% 50.0 52.9 53.2 53.6 53.9
4.% 48.1 51.0 51.3 51.7 52.1
............... Kerry Margin
12% 4.6 11.8 12.8 13.6 14.6
11% 3.7 10.9 11.8 12.7 13.6
10% 2.7 10.0 10.9 11.8 12.7
9.% 1.8 9.0 9.91 10.8 11.7
4% -2.9 4.3 5.18 6.08 7.00

..........Returning Gore Voter Turnout
Bush 94.% 95.% 96.% 97.% 98.%
Turnout..... Kerry % Vote Share
96% 53.4 53.5 53.7 53.8 53.9
97% 53.2 53.3 53.5 53.6 53.8
98% 53.0 53.2 53.3 53.4 53.6
99% 52.8 53.0 53.1 53.3 53.4
100% 52.7 52.8 52.9 53.1 53.2
............... Kerry Margin
96% 10.3 10.7 11.0 11.4 11.8
97% 9.86 10.3 10.6 10.9 11.3
98% 9.42 9.78 10.1 10.5 10.9
99% 8.97 9.33 9.69 10.1 10.4
100% 8.52 8.88 9.24 9.60 9.96

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Posted by on February 5, 2013 in Uncategorized


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1968-2012 Presidential Election Fraud: An Interactive True Vote Model Proof

1968-2012 Presidential Election Fraud: An Interactive True Vote Model Proof

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.


Posted by on January 24, 2013 in True Vote Models, Uncategorized


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Track Record: 2004-2012 Election Forecast and True Vote Models

Track Record: 2004-2012 Election Forecast and True Vote Models

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

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Posted by on January 19, 2013 in Uncategorized


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

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

Richard Charnin
Updated: Oct.28, 2013

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

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

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

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

The Law of Large Numbers

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

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

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

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

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

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

Winnebago County


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