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2016 Pre-election Polls in 16 Battleground states were biased for Clinton

Richard Charnin
Sept.15, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll
Reclaiming Science: The JFK Conspiracy
LINKS TO  POSTS
Last 3 Elections: Exact Forecast of Electoral Vote

In 16 battleground states, Trump won the recorded vote by 48.0-45.9%, a 2.1% margin. Clinton led the pre-election polls by 44.5-44.1%, a 0.4% margin.

When undecided voters are allocated (UVA), Trump leads the 16-poll average 46.6-45.3%. Using the Gallup National Voter affiliation survey (40Ind-32Dem-28Rep) to derive each state’s Party-ID, Trump leads 48.9-43.1%.

Clinton won the 16 unadjusted exit polls 47.4-45.6%, a 1.8% margin.

There was a 2.5% average margin discrepancy between the pre-election 16-poll average and the corresponding recorded vote average. The 4.6% difference between the 2.5% discrepancy and the 2.1% national recorded margin is an indicator that the pre-election polls were biased for the Democrats.

In 10 final National pre-election polls, Clinton led 46.8-43.6%, a 3.2% margin. She won the National recorded vote by 48.3-46.2%, a 2.1% margin.

Summary of 16 Battleground states:
Unweighted averages:
Clinton won the pre-election polls by 44.5-44.1%.
Clinton won the unadjusted exit polls by 47.4-45.6%
Trump won the recorded vote by 48.0-45.9%.
Trump won the UVA-adjusted polls by 46.6-45.3%.
Trump won the Gallup Party-ID adjusted polls by 48.9-43.1%.

Weighted averages (56.8 million votes):
Clinton won the pre-election polls by 45.0-44.7%.
Clinton won the unadjusted exit polls by 47.5-46.1%
Trump won the recorded vote by 48.4-46.1%.
Trump won the UVA-adjusted polls by 47.0-45.7%.
Trump won the Gallup Party-ID adjusted polls by 48.5-43.9%.

Battleground Exit poll discrepancies:
Recorded vote:3.9%; UVA:3.1%; Pre-election polls:1.4%; Gallup:7.6%
UVA: Undecided Voter Allocation: Trump won the recorded vote by 48.0-45.9%.

Trump likely won the national vote by 48-44% (5 million votes).

https://richardcharnin.wordpress.com/2017/08/28/2016-true-vote-models-in-confirmation-party-id-and-returning-2012-voters/

Real Clear Politics (RCP)is the data source for the pre-election polls:
https://www.realclearpolitics.com/epolls/latest_polls/state/

View the data and calculations for the 16 state polls, recorded votes, unadjusted exit polls and undecided voters: https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=1579502018

 Trump Pre-elect UVA Recorded Exit polls
True Vote
AZ 46.3 48.3 48.1 46.9 50.7
CO 40.4 44.3 43.3 41.5 48.9
FL 46.6 48.1 48.6 46.4 48.0
GA 49.2 50.0 50.5 48.2 52.6
IA 44.3 47.6 51.2 48.0 52.1
ME 39.5 44.5 44.9 40.2 48.6
MI 42.0 45.4 47.3 46.8 47.1
MN 39.0 40.8 44.9 45.8 46.5
MO 50.3 52.0 56.4 51.2 51.4
NV 45.8 47.2 45.5 42.8 47.1
NH 42.7 45.9 46.5 44.2 51.1
NC 46.5 49.2 49.9 46.5 46.3
OH 45.8 48.3 51.3 47.1 50.1
PA 44.3 47.2 48.2 46.1 45.6
VA 42.3 44.6 44.4 43.2 48.4
WI 40.3 42.9 47.2 44.3 47.4
AVERAGE 44.1 46.6 48.0 45.6 48.9

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Posted by on September 15, 2017 in 2016 election

 

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2016 Pre-election Model – Calculating the Expected Electoral Vote

Richard Charnin
Aug. 29, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll
Reclaiming Science: The JFK Conspiracy
LINKS TO  POSTS
Last 3 Elections: Exact Forecast of Electoral Vote

2016 Pre-election Model – Calculating the Expected Electoral Vote

This is for those interested in Electoral Vote math based on pre-election polls. It discusses basic probability and spreadsheet functions. You won’t see a discussion of this anywhere else.The MSM doesn’t care for critical thinking. Perhaps because they are incapable of it.

One of the methods I have used in pre-election forecast modeling is to calculate the Expected Recorded Electoral Vote as well as the True Vote. Important Note: the RECORDED EV is based on MSM pre-election polls which are usually biased for the establishment candidate. In 2016, Clinton was the establishment candidate.

As I did not have 51 state pre-election polls, I used the following method to estimate them based on the average of nine pre-election national polls and Party-ID:

1) Each state’s estimated Party-ID was calculated using the proportional change from the 2012 National Party-ID to the 2016 Gallup National Voter affiliation survey: 40% Independents, 32% Democrats and 28% Republicans.

2) The average vote shares of nine national pre-election polls were applied to the Party-ID of each state to derive the projected state vote shares.

The Expected EV is based on state win probabilities. Calculating the pre and post-election TRUE EV is much more complicated.

In the 2016 Forecast Model, Trump’s Expected EV (before undecided voters) was 305.5, exactly matching his recorded 306 EV. His Snapshot 307 EV is the sum of the EVs for states that he was projected to win. Trump led the weighted average pre-election polls (before undecided voter allocation) by 44.1-43.1%.

View the Recorded votes and two True Vote Models for all the states:
https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=667189511

The following steps calculate the Expected RECORDED EV:
1. Using state forecasts derived from the National Gallup Voter Affiliation survey, calculate the probability P(i) of winning each state using Trump’s projected 2-party vote share. Assume a 3.0% margin of error.
P(i) = normdist(Trump%/(Trump%+Clinton%),0.5,.03/1.96,true)

2. Multiply the state win probability by the state electoral vote.
S(i) = P(i)* EV(i), i =1,51
3. Expected EV = sum [P(i)* EV(i)], i = 1,51

View the spreadsheet https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=1036175945
State Electoral votes are in the range B129:B179
Trump’s state forecasts are in the range D129:D179
Corresponding state win probabilities are in the range J129:J179

The Expected EV calculation is in cell I128.
Expected EV = 305.5 = sumproduct(J129:J179, B129:B179)

 

 
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Posted by on August 29, 2017 in 2016 election, electoral vote

 

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2016 True Vote Models in Confirmation: Party-ID and Returning 2012 Voters

2016 True Vote Models in Confirmation: Party-ID and Returning 2012 Voters

Richard Charnin
Aug.28, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll
Reclaiming Science: The JFK Conspiracy
LINKS TO  POSTS
Last 3 Elections: Exact Forecast of Electoral Vote

Pollsters no longer ask the question “How did you vote in the last election”? Why? Because posing the question provides an analyst with data to indicate election fraud.

In 1972, 1988, 1992, 2004 and 2008, in order to match the recorded vote (SOP), the exit pollsters (who work for the MSM) required a greater turnout of Bush voters from the prior election than were still alive. This is a MATHEMATICAL IMPOSSIBILITY. If the exit poll is impossible, the recorded vote it was forced to match must also be impossible. That is proof of fraud. It’s why the exit pollsters (the MSM) no longer ask the question “Who Did You Vote for in the Last Election”?

The Exit Poll Smoking Gun: “How did you vote in the last election”?

These 2016 models calculate a true vote estimate for each state.
Model 1: Obama and Romney voter turnout in 2016.
Model 2: Gallup Party-ID voter affiliation. Used in the 2016 forecast model.

Base case vote shares were identical in each model. The shares were forced to match the recorded vote assuming equal 95% turnout. To calculate the True Vote, returning Obama voter turnout in 2016 was adjusted to 89%. The assumption is that 6% of Obama voters were Bernie Sanders 2016 primary voters who did not return to vote in the presidential election.

Important note: Since the vote shares were forced to match a likely fraudulent recorded vote (the Mainstream Media was heavily biased for Clinton), the following results are conservative. Trump probably did at least 2% better than indicated in the base case calculations. View the sensitivity analysis.

So how can we determine Obama and Romney returning voter turnout in 2016? Where can we get that information? Why don’t the exit pollsters provide the data? Should we just guess or estimate turnout based on historical elections? I chose the latter.

Using the prior 2012 vote as a basis, a voter mortality estimate is factored in. Approximately 4% of voters pass between each election (1% annual mortality). The simplest approach is to assume an equal 95% turnout of Obama and Romney voters still living. Now we have a plausible approximation of the (unknown) mix of returning voters. Since we know the current election recorded vote, the number of new 2016 voters who did not vote in 2012 can be calculated: DNV = 2016 total vote – returning 2012 voters.

The first step is to force the candidate shares of returning voters to match the recorded vote assuming equal 95% turnout.

In the True Vote calculation, the percentage of returning Obama voters was lowered to 89% to reflect disenchantment among Bernie Sanders’ primary voters who did not vote in the general election or voted for Jill Stein or Donald Trump.

To view the sensitivity of the True Vote to Trump shares of returning Obama and Romney voters, a matrix of total vote shares is calculated in 1% increments around the Trump base case estimate. There are 25 vote share scenario combinations in the 5×5 matrix. Corresponding matrices of Clinton shares and vote margins are also included. The base case is in the central cell.

2016 Presidential State Election Model Summary
https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=667189511

Recorded Vote
Clinton: 48.25-46.17% (2.83 million votes)
Trump: 306 Electoral Votes

Model 1
(returning 2012 voters)
2012 recorded vote: Obama 51.03-Romney 47.19% (4.98 million)
2016 voter turnout: Obama 89%, Romney 95%
Trump: 47.8-46.7% (1.51 million votes)
Trump: 323 Electoral Votes

Model 2
Gallup National Voter Affiliation Survey: 32D-28R-40I (state adjusted)
1. Trump and Clinton split the undecided vote:
Trump: 46.8-45.8% (1.35 million votes)
Trump: 307 Electoral Votes

2. Trump had 75% of the undecided vote:
Trump: 48.1-44.5% (4.97 million votes)
Trump: 352 Electoral Votes

The National Model
https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=1768941212

Vote share sensitivity analysis (Model 1)
-Best case: Trump had 92% of returning Romney voters and 9% of Obama voters
Trump by 49.4-45.0% (5.98 million votes)
-Base case: Trump had 90% of returning Romney voters and 7% of Obama voters
Trump by 47.8-46.7% (1.51 million votes)
-Worst case: Trump had 88% of returning  Romney voters and 5% of Obama voters
Clinton by 48.3-46.1% (2.97 million votes).

Mathematical Proof: the 2004 election was stolen
The 2004 National Exit Poll was impossible as it was forced to match the recorded vote (Bush 50.7-48.3%) using an impossible number of returning Bush 2000 voters. It indicated that 52.6 million (43% of the 2004 electorate) were returning Bush 2000 voters and just 45.3 million (37%) were returning Gore voters. But Bush had just 50.5 million recorded votes in 2000. It indicated an impossible 110% turnout of living 2000 Bush voters in 2004.

2004 Election Fraud
https://richardcharnin.wordpress.com/2015/10/30/2004-election-fraud-overwhelming-statistical-proof-that-it-was-stolen/

2004 Spreadsheet 1
https://docs.google.com/spreadsheet/ccc?key=0AjAk1JUWDMyRdFIzSTJtMTJZekNBWUdtbWp3bHlpWGc&usp=sheets_web#gid=7

2004 Spreadsheet 2
https://docs.google.com/spreadsheets/d/1x2WCPJautd_eZPIfkmW9W9vD2p1Zu0ZlvgqV_gUwLNM/edit#gid=13

 
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Posted by on August 28, 2017 in 2016 election, True Vote Models

 

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2016 State Presidential True Vote Model

2016 State Presidential True Vote Model

Richard Charnin
Aug. 25, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Exit Poll
Reclaiming Science: The JFK Conspiracy
LINKS TO  POSTS
Last 3 Elections: Exact Forecast of Electoral Vote

This is an analysis of the presidential vote in each of the 50 states and DC. To view the calculations for any state, just click the State tab. No input is required.

Since the 2012 election,  exit pollsters no longer provide the crosstab Who did you vote for in the previous election?  Like all crosstabs, it was matched to the recorded vote.  The  Trump, Clinton and 3rd party shares of returning Obama and Romney voters are not available. However we can closely approximate the crosstab  by calculating the shares required to match the recorded vote.

National Result
Clinton won the recorded vote by 2.87 million (48.25-46.14%).
Trump had 306 electoral votes.
Trump won the True Vote by 1.69 million (47.61-46.37%). He had 323 electoral votes.

Note:  Trump must have done better than the model indicates, since it uses vote shares derived to match the recorded vote that was biased for Clinton.

Assumptions

  • Recorded vote: 95% turnout of Obama and Romney voters in 2016. Vote shares are forced to match the state recorded vote.
  • True Vote: 89% turnout of Obama voters and 95% turnout of Romney voters.  Vote shares remain the same as used in the recorded vote.  The assumption is that 6% of Obama voters who were for Bernie Sanders in the primary did not return to vote in the presidential election. But an unknown number voted for Jill Stein and Donald Trump.

View the data and calculations for each state.  For instance, click the FL tab.
https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=517146616 

This sheet contains a Recorded and True Vote summary for  each state.  https://docs.google.com/spreadsheets/d/10dlTnin814phKJWjYdkG-ujNKak3zo6ywIP0u0-TGFg/edit#gid=667189511

Sensitivity Analysis
To see the effects of  changes in returning vote share assumptions, view the Sensitivity Matrix. It contains 25 scenarios of Trump and Clinton vote shares in one percent increments above and below the base case. The base case is the central cell  of the matrix.

Note: the difference between Recorded and True Vote is assumed strictly due to 2012 voter turnout in 2016. Granted, this is a simplifying assumption which is obviously not the case for each state.

 
 

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2016 Election Model- 9 pre-election polls: 5 Non-MSM and 4 MSM pollsters

Richard Charnin
Aug, 4, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

The following are the basic steps used to estimate 2016 National True Vote shares.  The True Vote Model utilizes nine  pre-election polls.  Party-ID varies greatly among the polls. Therefore, Gallup’s dedicated voter affiliation (Party-ID) survey is used to adjust the national poll shares.

The 2016 Gallup national survey is used to approximate state Party-IDs by calculating the change from 2012 National Party-ID to 2016 Gallup Party-ID.  The projected state vote share is calculated by applying the average of the 9 national pre-election Party-ID poll shares to the 2016 state Party-ID. The electoral vote is then calculated. View the full set of calculations in this spreadsheet: https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1036175945

National True Vote Model: Basic Methodology

1) Compare MSM vs. non-MSM polls (Party-ID and vote shares).
2) Adjust pollsters Party-ID to Gallup voter affiliation
3) Allocate undecided voters.
4) View the effect of these adjustments to the pre-election vote shares.

  • MSM pollsters overweighted Democrats Party-ID and underweighted Independents compared to non-MSM pollsters. Clinton wins the polls by 45.8-43.6%, matching her 2.1% recorded vote margin.
  • 2 Apply Gallup voter affiliation survey of National Party-ID (40I-32D-28R)  to each of the nine polls, Trump is a 44.1-43.3% winner.
  • 3 Note: the polls did not allocate undecided voters (approximately 6%), which typically break 3-1 for the challenger. Trump was the de-facto challenger.
  • 4 Effect: Allocating  undecided voters (4.5% to Trump and 1.5% to Clinton) to the Gallup-adjusted vote shares, Trump is the winner by 48.6-44.8%.

Non-MSM………….Party-ID…………..Pre-election……….Gallup (40I-32D-28R)
Polls………………Ind Dem Rep…….. Clinton..Trump…..Clinton Trump
IBD………………..37% 34% 29%…….. 43%….45%……..41.9% 45.3%
Rasmussen……..32% 40% 28%………45%….43%……..40.6% 45.3%
Quinnipiac………26% 40% 34%………47%….40%……..44.7% 40.8%
Gravis……………27% 40% 33%………47%….45%……..43.6% 45.5%
USC/Dormsite… 30% 38% 32%………44%….47%……..41.7% 48.2%
Average………..30.4% 38.4% 31.2%…45.2%.44.0%…..42.5% 45.0%

MSM……………..Party-ID……………..Pre-election…….Gallup Adj
Polls…………….Ind Dem Rep………..Clinton Trump..Clinton Trump
Reuters…………16% 45% 38%………42% ….39%…….36.0% 36.8%
Fox News………19% 43% 38%………48%…..44%…….45.8% 43.9%
CNN……………..43% 31% 26%………49%……44%…..48.6% 44.4%
ABC ……………..29% 37% 29%………47%…..45%……46.8% 47.0%
Average………26.8% 39.0% 32.8%…46.5% 43.0%……44.3% 43.0%

Summary…………….Party-ID…………Pre-election……Gallup Adj
…………………Ind…..Dem….Rep……Clinton.Trump..Clinton Trump
9 polls……….28.8% 38.7% 31.9%…..45.8% 43.6%…..43.3% 44.1%
5 nonMSM….30.4% 38.4% 31.2%…..45.2% 44.0%….42.5% 45.0%
4 MSM………26.8% 39.0% 32.8%…..46.5% 43.0%……44.3% 43.0%

Allocating  undecided voters (4.5% to Trump and 1.5% to Clinton) to the Gallup-adjusted vote shares, Trump is the winner by 48.6-44.8%.

 
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Posted by on August 5, 2017 in 2016 election, True Vote Models

 

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Adjusted Pre-election polls in the True Vote Model indicate Trump won by 5 million votes

Richard Charnin
Aug.2, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

This analysis shows that although Clinton won the Recorded Vote by 48.3-46.2% (2.8 million votes), Trump won the True Vote.

Plausible adjustments made to nine pre-election polls in the True Vote Model are the core of the analysis. These polls had Clinton winning by 45.8-43.6% with 298-240 electoral votes: Ipsos/Reuters, IBD/Tipp, Rasmussen, Quinnipiac, Fox News, CNN, ABC, Gravis, LA Times.

Adjusting  Party-ID to the Gallup voter affiliation survey, Trump won by 43.4-43.1% with 306-232 Electoral votes. After allocating 75% of undecided voters to Trump, the de-facto challenger, the True Vote Model indicates that Trump won  by 48.2-44.5% (5.1 million votes) with 336 electoral votes . Historically, challengers won a solid majority (65-90%) of undecided voters when the incumbent was unpopular. Clinton and the Democrats were unpopular, especially after she stole the primary from Bernie Sanders.

View the Model
https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1036175945

Model Results
Pre-election poll averages based on:
Party-ID: Clinton 45.8-43.6
Gallup voter affiliation: Trump 43.4-43.1

Forecast Model (post-UVA)
Party-ID (9 Pre-election poll average):  Clinton 46.7-46.2
Gallup Party-ID: Trump 48.2-44.5

Trump Electoral votes: Pre and post UVA
Snapshot EV: pre-UVA: 306 (exact forecast); post-UVA EV: 336

Expected EV based on state win probabilities
Pre UVA: 289; post UVA: 351

Method
Calculate the average of 9 final pre-election polls (Party-ID and vote shares).
Calculate National Vote shares using Party-ID from

  • 9-poll average: 28.9I-38.7D-31.9R
  • Gallup voter affiliation survey: 40I-32D-28R

Gallup Voter Affiliation
1- Nov. 1-6: 36I, 31D, 27R (6 other)
2- Nov. 9-13: 40I, 30D, 27R (3 other)
Average (Election Day) : 38I, 30.5D, 27R (4.5 other)

Calculate State Vote shares
State Party-ID based on proportional change in National Party-ID from 2012 to 2016 Gallup survey applied to 2012 State Party-ID.
2012: 40.3D, 35.4R, 24.7I  
2016: 32D, 28R, 40I

Undecided voter allocation (UVA): 75% to Trump

Sensitivity Analysis
15 vote share/margin scenarios (pre-UVA) based on Trump % of Rep and Ind
Best Case: Trump 45.0-42.7
Base Case: Trump 43.4-43.1
Worst Case: Clinton 43.5-41.9

Electoral Vote Scenarios
Recorded EV = 306
Forecast  EV (pre-UVA) = 306
Forecast True EV (post-UVA) = 336
Difference between 306 EV and 336 EV due to MI (16) and NJ (14)

Expected EV
(based on state win probabilities post UVA)
EV = 351
Exp EV = sum [(P(i) * EV(i)], i= 1, 51
(P(i) = probability of winning state, EV(i) =  State Electoral vote
Margin of Error (MoE) = 2.5%

 
 

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Seth Rich/DNC Mortality Probability

Richard Charnin
Updated: 5/26/19

LINKS TO  BLOG POSTS

There were at least n=19 suspicious DNC/Wikileaks deaths in 28 months from April 2016 to Aug 2018. 

The  Poisson distribution function calculates the probability of rare events. The probability P of at least n homicides  among a group of N individuals in T= 28 months (28/12 years), homicide rate  R=0.00005:

 P  = 1- poisson (n-1, E, true) where E=N*R*T

Assuming a total of N=20,000  DNC/Wikileaks related individuals, the probability of at least 19 homicides is 1 in 113 billion. Only 2 would be expected.

Assuming N=10,000, the probability of at least n=19 homicides is 1 in 20,000 trillion. Only 1 homicide would normally be expected.

You can run the spreadsheet calculator for any combination of N, n, R and T. https://docs.google.com/spreadsheets/d/1htajNqLQrV9M4jmwWUN7MweelfN2ZCwr8KB-YeO7r10/edit#gid=0

2016 (10)
4/18: John Jones, lawyer who defended Assange, run over by train.
5/11 : Michael Ratner (Wikileaks NY lawyer), cancer.
6/22: John Ashe, former UN official due to testify against HRC (barbell accident).
6/23: Mike Flynn,48, died day he reported on Clinton Foundation (unknown).
7/10: Seth Rich, DNC e-mail leaker to Wikileaks, shot twice in back, died in hospital.
7/25: Joe Montano,47, DNC, heart attack day before the DNC convention.
8/01: Victor Thorn, gunshot wound, author of books on Clintons.
8/02: Shawn Lucas, DNC process server, lethal combination of drugs.
Oct : Gavin McFayden (Wikileaks founder), cancer.
Nov : Monica Petersen, investigator of Clinton Foundation, child trafficking, found dead in Haiti.

2017 (7)
May: Peter Smith, GOP operative, found dead from asphyxiation in a Minnesota hotel room just days after talking to the Wall Street Journal about his efforts to obtain Hillary’s Clinton’s missing emails.
May: Beranton Whisenant, prosecutor investigating DNC, found dead on Hollywood, FL beach.
July: Klaus Eberwein, former Haiti Government official found dead in a motel room with a gunshot wound to the head. Was to testify on Clinton Foundation connection to Haitian earthquake charity.
July: Joseph Rago, 34, WSJ reporter, asked Russians for info on Clinton,  Obama critic, found dead.
Aug: Kurt Smolek, ties to PizzaGate and child trafficking ring in Cambodia, found dead in Potomac River.
Nov: Steve Mostyn, 46, Texas-based trial lawyer,  member of George Soros-founded Democracy Alliance, major Democratic benefactor, died suddenly. Called suicide.
Dec: Dr. Dean Lorich, surgeon, exposed Clinton Foundation corruption in Haiti, stabbed in chest. Called suicide.

2018 (2)
Jan: James Dolan, 36, Wikileaks developer. Suicide.
Aug: Jen Moore, journalist of Clinton sex crimes, found dead in a DC hotel.

How many DNC voter data admins were there? How many DNC process servers? How many HRC biographers? How many Assange lawyers? How many Wikileaks founders? How many UN officials preparing to testify? How many DNC officials? How many investigative reporters on the Clintons? Are any of these deaths being investigated? Any suspects?

Probability Matrix of n homicides in a group of N over 28 months (2.33 years)

n N=20,000 30,000 40,000 50,000 60,000 70,000
6 3.18% 14.24% 32.58% 52.72% 69.93% 82.36%
9 0.07% 0.99% 4.85% 13.60% 27.09% 43.07%
12 0.00% 0.03% 0.32% 1.66% 5.33% 12.43%
15 0.00% 0.00% 0.01% 0.11% 0.57% 2.03%
19 0.00% 0.00% 0.00% 0.00% 0.01% 0.08%
1 in Probability 
19 113 billion 153 million 1.9 million 83,000 7.700 1,200

http://www.thegatewaypundit.com/2018/03/insider-ed-butowsky-seth-richs-father-told-knew-sons/

Subpoenas issued for FBI, Crowdstrike and DNC : http://lawflog.com/?p=2177&fbclid=IwAR3AL2hiqAmRTo9B6oSCpeaBvCcuvI4NGTUcRrHGG5kwDOpCDqDx3jVKOsI

NSA FOIA Response reveals Seth Rich & Assange/Wikileaks communications are Classified

………………………………………………………………….

JFK WITNESS DEATHS

In 1964-78, there were an estimated 1500 JFK-related material witnesses, of whom 122 died suspiciously. Seventy-eight(78) of the 122 were officially ruled unnatural. Of the 78, 34 were homicides, 24 accidents, 16 suicides and 4 unknown. The probability of 78 unnatural deaths:P= 2.7E-31 (1 in a million trillion trillion).

Just 12 accidents and 3 suicides were expected statistically, therefore approximately 60 of the 78 unnatural deaths were likely homicides.

Of the remaining 44 “natural” deaths (heart attacks, sudden cancers, other), approximately 25-30 were homicides based on the total number of expected deaths. Therefore, there were 85-90 homicides among the 122 suspicious deaths. For 10,000 witnesses, Probability P= 5.5E-47

<https://richardcharnin.wordpress.com/2013/02/25/executive-action-jfk-witness-deaths-and-the-london-times-actuary/
https://docs.google.com/spreadsheets/d/1FmXudDf6pqisxq_mepIC6iuG47RkDskPDWzQ9L7Lykw/edit#gid=3

Simkin JFK Index of 656 key individuals: 70 suspicious deaths
44 ruled unnatural (22 homicides, 11 accidents 11 suicides): P= 4.4E-41
Assuming 44 were homicides: P= 3.8E-66

https://docs.google.com/spreadsheets/d/1FmXudDf6pqisxq_mepIC6iuG47RkDskPDWzQ9L7Lykw/edit#gid=81

 
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Posted by on May 20, 2017 in 2016 election, JFK, Uncategorized

 

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