Conspiracy Theories and Mathematical Probabilities

Conspiracy Theories and Mathematical Probabilities

May 25, 2012

Richard Charnin

It is an interesting exercise to calculate mathematical probabilities of so-called “conspiracy theories”. The mainstream media and their cadre of online gatekeepers use the term “Conspiracy Theorist” (CT) as a derogatory label for those who seek the truth. According to the media, there are never conspiracies. But they avoid factual discussions based on the scientific evidence.

These myths are promoted non-stop in the mainstream media.
- Oswald acted alone in 1963 – with a magic bullet and defective rifle.
- Bush won Florida in 2000 and had a 3 million “mandate” in 2004.
- Nineteen Muslims armed with box cutters who could not fly a Cessna, hijacked four airliners and outfoxed the entire U.S. defense establishment – while Bin Laden was on dialysis, near death and hiding in caves.

But the media can’t refute the mathematics that proves beyond a reasonable doubt that there is a massive conspiracy to hide the truth of these events from the public.

Scientific notation is necessary to express the extremely low probabilities of the following events. For example, the probability P that at least 15 material witnesses would die unnaturally in the year following the JFK assassination is 0.000000000000006 or 1 in 167 trillion. There are 15 zeros to the right of the decimal point (represented in short-cut scientific notation as 6E-15).

To put the numbers in context: There are an estimated 3 billion trillion (3E23) stars in the universe. That’s 3 followed by 23 zeros: 300,000,000,000,000,000,000,000. There are an estimated 700 thousand trillion (7E17) grains of sand on earth or 7 followed by 17 zeros: 700,000,000,000,000,000.

The probability calculations are based on the Normal, Binomial and Poisson distribution functions.

The Normal Distribution (ND) is based on a sample of observations defined by the mean (average) value and standard deviation (a measure of volatility of the observations from the mean). The ND is used to calculate the probability P that Kerry’s unadjusted 51.7% National Exit Poll (13660 respondents) share would deviate 3.4% from his 48.3% recorded national share.

The Binomial Distribution (BD) is used to calculate the probability P of n successes in N trials when the probability p of a success is constant in each trial. The BD is used to calculate the probability P that n= 86 of N=88 DRE voting machines would flip votes from Kerry to Bush (p =0.50).

The Poisson Distribution (PD) is used to calculate the probability P that a given number n of events with low probability p will occur over a period of time. The PD is used to calculate the probability P that at least n JFK-related individuals out of a population of N witnesses would die unnaturally in the years following the assassination.

The probability of an individual dying unnaturally (murder, accident, suicide, unknown) in any given year is approximately 0.000542.

Unnatural JFK-related Witness Deaths

The probability analysis is straightforward; it is not a theoretical exercise. It is a mathematical proof of conspiracy based on factual data (number of witnesses, number of unnatural deaths, corresponding mortality rates, time period). The Poisson function calculates the probability. 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 database of witnesses, the unnatural mortality rates and the use of the Poisson formula.

This is a spreadsheet database of witnesses and probability calculations.

Warren Commission Witness Deaths

There were 552 witnesses who testified at the 1964 Warren Commission.

1964-1966
There were 11 suspicious deaths of Warren Commission witnesses in the three years (1964-1966) following the assassination: 3 murders, 1 attempted murder, 1 suicide, 3 motor accidents, 2 sudden cancers, 1 heart attack. The weighted average mortality rate is 0.000179. P = 1 in 910 MILLION. Assuming the 8 unnatural deaths were homicides, P= 1 in 3.6 TRILLION. But the probabilities are conservative. The sudden cancers were likely homicides.

Assuming the 10 deaths were homicides, P = 1 in 31 THOUSAND TRILLION (in the same ballpark as the actuary’s 100,000 TRILLION to 1 odds of 18 material witness deaths in three years).

1964-1977
At least 14 of the 552 died unnaturally in the fourteen year period (3 suicides, 5 homicides, 6 accidents. Four (4) would normally be expected). Given the 0.000542 unnatural death rate, the probability P is:
P = 1-Poisson (13, 14*552*.000542, true)
P = 1 in 10 MILLION.

If the “suicides” and “accidents” were actually homicides, then given the 0.000062 homicide rate, the probability of at least 14 homicides is P = 1 in 2 THOUSAND TRILLION.

Material Witnesses

In the year following the assassination, 15 of 1400 JFK-related witnesses died from unnatural causes (one would normally be expected). The probability that at least 15 would die unnaturally:
P = 6E-15 = 1-Poisson (14, 1400*.000542, true)
P = 1 in 167 TRILLION.

In the three years following the assassination, at least 33 of 1400 JFK-related witnesses died from unnatural causes (one would normally be expected). The probability that 33 would die unnaturally:
P = 7.3E-27 = Poisson (33, 3* 1400*.000542, false)
P = 1 in 137 TRILLION TRILLION.

In the 1964-1977 period, at least 70 of 1400 JFK-related individuals died unnaturally (10 expected).
The probability of exactly 70 unnatural deaths:
P = 1.4E-33 = Poisson (70, 14*1400*.000542, false)
P = 1 in 715 MILLION TRILLION TRILLION.

1988-2008 Election Fraud

1. In 2004, the Election Incident Reporting System (EIRS) indicated that 86 of 88 DRE voting machines in various states flipped votes from Kerry to Bush. The probability P is calculated as:
P = 1E-23 = Binomdist (86, 88, .5, false) + Binomdist (87, 88, .5, false) + Binomdist (88, 88, .5, false)
P = 1 in 79 billion trillion

There were massive discrepancies between the average Democratic/Republican recorded vote split (48-46%) and the 274 unadjusted state and national exit polls (52-42%). The True Vote Model (TVM) was developed before the exit polls were posted on the Roper UConn website. The 53-41% TVM split confirmed the polls.

2. In 2008, the unadjusted exit polls in 36 states red-shifted beyond the margin of error (MoE) to McCain in the recorded vote.
P = 2.4E-39 = Poisson(36,.025*50,false)
P = 1 in 400 trillion trillion trillion!

3. In the 1988-2008 presidential elections, 226 (82.4%) of the 274 exit polls red-shifted to the Republican. Normally, an even split (137) would be expected. The probability is:
P = 3.7E-31 or 1 in 2.7 million trillion trillion!

4. The probability that at least 55 of 57 state elections would flip from the Democrats in the polls to the Republicans in the recorded vote is given by the Binomial distribution:
P = 1-Binomdist(54,57,.5,true)
P = 1.1E-14 = 0.000000000000011 or 1 in 88 trillion!

5. In the 1988-2008 elections, there was an 8% discrepancy between the 274 state unadjusted exit poll aggregate (52D-42R) and the recorded votes (48D-46R). There were 375,000 exit poll respondents. Assuming an extremely conservative 1.2% margin of error, the probability of the discrepancy is:
P = Normdist(.52,.48,.012/1.96,false) = 3.51E-08 or 1 in 28 million.
Assuming a plausible 0.8% MoE, the probability is P= 1.37E-19 or 1 in 7 million trillion!

6. The exit poll margin of error (MoE) was exceeded in 123 of the 274 exit polls in favor of the Republican – and just 3 for the Democrat. The probability that the MoE would be exceeded in any state is 1 in 20. Therefore, the MoE would normally be expected to be exceeded in 7 states for the Republican and 7 for the Democrat.

The Poisson function calculates the probability that the margin of error would be exceeded in 123 of 274 state exit polls in favor of the Republican:
P = 5E-106 = Poisson (123, .025*274, false)

P = .0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 000005

Microbiologist Mystery Deaths

The unnatural deaths of sixteen world-class microbiologists in the four months following 9/11 and the anthrax scare cannot be coincidental. Assuming there are 10,000 world-class microbiologists, the probability of 16 unnatural deaths in 4 months is:
P = Poisson(16,.33*.000542*10000,false)
P = 8.77E-11 or 1 in 11 billion!

9/11 Scientific Evidence vs. the Official Conspiracy Theory

To believe the official conspiracy theory (OCT) requires a belief in miracles. It requires cognitive dissonance of obvious explosive (WTC1 and WTC2) and symmetric (WTC7) destruction.

Probability calculations are not applicable as free-fall collapse is physically impossible without explosives. Ask Isaac Newton. Office fires burn at 2000 degrees below the temperatures required to melt steel. Not one steel-framed building has ever collapsed due to fires, before or since 9/11. The probability is ABSOLUTE ZERO based on historical facts and Newtonian physics.

1. NIST claims that office fires caused 3 steel-framed buildings to collapse at near free-fall – a clear refutation of Newton’s Laws of Motion.
- Free fall can only occur by an instantaneous removal of all supporting columns (i.e. a controlled demolition).
- Lateral ejection of debris can only occur from explosions – not from fires.
- Jet fuel fires burn at a much lower temperature than is required to melt steel.
- No steel-framed office buildings have ever collapsed due to fires.

2. CNN reporter Barbara Olson was a passenger on AA Flight 11 (which allegedly crashed into the Pentagon). She called husband Solicitor General Ted Olson from her cell phone and told him hijackers were armed with knives and box cutters.
- It was later disclosed that cell phones could not work at 30,000 feet.
- Olson then said that she called from a seatback phone. But according to an American Airlines spokesman, there were no seatback phones on Boeing 757 airliners.
- At the 2006 Moussaoui trial, the FBI reported there was one attempted call that lasted zero seconds (“unconnected”)from Barbara Olson to Ted Olson.

3. The BBC reported that WTC 7 collapsed at 5pm, 20 minutes before happened.
- How did the reporter know that it would collapse? Was she psychic?
- All fires burned out long before 5pm.
- Silverstein, the owner, said “pull it”.

and there is much more…

If you believe the official story (OCT), then what is your estimate of the probability of the following facts?

- William Rodriguez, a WTC janitor, would hear a loud explosion seven seconds before the plane hit, but his testimony would be ignored by the 9/11 commission.
- The NIST would fail to acknowledge free-fall until David Chandler proved it.
- The collapse of WTC 7 would occur due to structural failure of one beam.
- The 9/11 Commission would fail to mention WTC 7 or note it their Report
- For the first time in history, not one but three steel-framed buildings would collapse due to office fires.

- Airline fuel burning at 1000F would melt steel.
- April Gallop would hear an explosion next to her office at the Pentagon but not see any aircraft debris.
- NIST would not consider explosives as a possible cause of the collapses.
- NIST would admit freefall and claim it was due to office furniture fires.
- There would be traces of thermite in the lungs of first responders.

- Over 118 firefighters would imagine that they heard explosions.
- Furniture would be ejected laterally 600 feet from office fires.
- Firefighters would know that WTC 7 would collapse before it did.
- When Larry Silverstein said “pull-it” he did not mean demolish WTC 7.
- At 5pm, the BBC would report WTC7 fell, 20 minutes before it did.

- The passport of an alleged hijacker would be found in the rubble of the WTC.
- There would be no manifest record that hijackers boarded the planes.
- Put options on airline stocks would rise dramatically a few days before 9/11.
- Osama Bin Laden would not be on the FBI most wanted list for 9/11.
- 9/11 Commission heads Kean and Hamilton would disavow their own report.

- There were multiple air defense exercises conducted on 9/11.
- Officials who ignored standard response procedures would be promoted.
- Not one of the four flight recorders would be retrieved.
- There is no video, airline debris or human remains at the Pentagon.
- There is no video, debris or human remains at the Pennsylvania crash site.

- The media would not investigate these facts.

 

The Walker Recall: Is the Past Prologue?

The Walker Recall: Is the Past Prologue?

Richard Charnin
May 24, 2012

In a previous Walker recall election analysis the Wisconsin True Vote Model indicated that Barrett would win a fair election with 53-54%. The purpose of this analysis is to determine what it took for Walker to win in 2010. This information may provide insight into what we can expect in the recall.

The 2010 Election

Approximately 69% of 2008 voters turned out in the 2010 Wisconsin Governor race. Walker defeated Barrett by 125,000 recorded votes (52.2-46.6%). The exit poll was forced to match the recorded vote. That is standard operating procedure.

In order to force the exit poll to match the vote, it required that 49% of the 2010 electorate were returning Obama voters and 43% returning McCain voters. The 6% spread is 8% below Obama’s recorded margin and a whopping 22% below his exit poll margin. The spread implies that 66% of Obama voters and 77% of McCain voters returned in 2010 – a net 11% turnout advantage to Walker.

In the poll, Barrett had 83% of Obama voters and 7% of McCain voters – a net 10% defection of returning Obama voters. Walker had 16% of Obama voters and 93% of McCain voters. In addition, 3% were returning third-party and 5% did not vote in 2008 – but the vote shares were n/a. A simple calculation shows that in order to match the recorded vote, Walker needed to win new and returning third-party voters by a 20% margin.

To summarize, in order to match the recorded vote, the adjusted Final 2010 Wisconsin exit poll assumed…
1) There was ZERO fraud in 2008.
2) McCain returning voter turnout exceeded Obama turnout by 11%.
3) 16% of Obama voters defected to Walker and 7% of McCain voters defected to Barrett.
4) Walker had a 20% margin among new and returning 2008 third-party voters.

The 2012 True Vote Model

The base case assumption in the 2012 Wisconsin Recall True Vote Model that Obama had a 60% vote share is conservative. He had 63.3% in the Wisconsin exit poll (2545 respondents) but just 56.2% recorded – triple the 2.4% margin of error. There is a virtual 100% probability that Obama’s True share exceeded 60%. In other words, the 2008 election was likely extremely fraudulent, but not so fraudulent as to cause Obama to lose Wisconsin.

Unlike final national and state exit polls that are adjusted to conform to the recorded vote (and implicitly assume zero fraud), the True Vote Model is based on a feasible estimated turnout of previous election voters and best vote share estimates of returning and new voters.

The model calculates various scenarios (“sensitivity analysis”) of 2008 election voter turnout in 2012 based on the 2008 a) recorded vote, b) unadjusted exit poll or 3) estimated True Vote.

What does this portend for the recall?
Three scenarios:

1) Fraud: Walker wins by a similar margin as he did in 2010 (125,000 votes)
2) Fraud: But not enough to steal the election. Barrett wins by 70,000.
3) No fraud. Barrett wins by at least 160,000.

1988-2008: the 8% unadjusted exit poll margin discrepancy

Unadjusted state and national exit poll data is available on the Roper website. The Democrats won the aggregate 1988-2008 presidential unadjusted exit polls by 52-42% -an 8% discrepancy in margin from the 48-46% recorded vote. Bloggers, pollsters and academics are apparently unaware that the data even exists. After all, the NY Times and CNN never reported that fact. But they do show exit polls adjusted to conform to bogus recorded votes on their websites.

How many voters are aware that Obama won the Unadjusted National Exit Poll (17,836 respondents) by a 61-37% margin? Or that he won the state aggregate exit polls (82,388 respondents) by 58-40.5%? The Final 2008 National Exit Poll was forced to match the recorded vote by implying an impossible 103% turnout of living Bush 2004 voters and 12 million more returning Bush than Kerry voters.

In every election the pollsters force state and national exit polls to match the recorded vote. They accomplish this by adjusting all demographic crosstabs that are displayed in the various mainstream media election sites. As a result of the forced match to the recorded vote, the “pristine” demographic percentages are contaminated. In other words, by matching to the recorded vote, final exit polls disguise the true intent of various classes of voters.

 

Wisconsin Governor Recall: A True Vote Model Analysis

Wisconsin Governor Recall: A True Vote Model Analysis

Richard Charnin
May 3, 2012

Barrett should win easily – assuming ZERO fraud.
But there WILL be fraud. So let’s look at the scenarios.

Let’s check out the Wisconsin True Vote Model.

In 2008, Obama had a 56.2% recorded vote share in Wisconsin. But he had 63.2% in the unadjusted exit poll (n=2,545 respondents). The poll had a 2.43% margin of error (including a 30% “cluster effect”).

MoE = (1+cluster) * Stdev * sqrt(p*(1-p)/n)
MoE = 2.43% = 1.3 * 1.96 * sqrt(.639*.361/2545)

There is a near 100% probability that Obama’s True Wisconsin share exceeded 60%:

All of the following scenarios assume that Obama had a 60% WI share.
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CONSERVATIVE Base Case assumptions (favoring Walker)

Returning 2008 Voter Turnout (net 5% to Walker)
65% Obama voter turnout
70% McCain voter turnout

Voter Defection (net 5% to Walker)
Barrett wins 90% of returning Obama voters
Barrett wins 5% of returning McCain voters

Barrett wins by 54.6-45.4% (198,000 votes)
Walker needs to steal 8.4% of Democratic votes to win.

___________________________________________________________________________

Zero Net Turnout and Voter Defection Scenarios

1. Equal 70% turnout; Barrett wins 90% of Obama and 5% of McCain voters
Barrett has 56.2% and wins by 267,000 votes.
Walker needs to steal 11% to win.

2. Equal 70% Turnout; Barrett wins 95% of Obama and 5% of McCain voters.
Barrett has 59% and wins by 387,000 votes.
Walker needs to steal 15% to win.
___________________________________________________________________________

Democratic Worst Case Scenarios

1. Voter Turnout: 65% of Obama; 70% of McCain
Barrett wins 85% of Obama voters and 0% of McCain voters.
Barrett has 50.2% and wins by 9,000 votes.

2. Voter Turnout: 60% Obama; 75% McCain
Barrett wins 90% of Obama voters and 5% of McCain voters.
Barrett has 51.8% and wins by 80,000 votes.

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Implausible Scenarios required for Walker to win a fair election

1. Voter Turnout: 55% Obama; 80% McCain
Vote share: Barrett wins 90% of Obama voters and 5% of McCain voters.
Barrett has 49.1% and loses by 38,000.

2. Voter Turnout: 65% Obama; 70% McCain
Vote share: Barrett wins 80% of Obama voters and 5% of McCain voters.
Barrett has 49.4% and loses by 25,000.