2016 National Exit Poll vs. Estimated True Vote. Did Jill Stein have just 1.45 million (1.07%) recorded votes?

2016 National Exit Poll vs. Estimated True Vote. Did Jill Stein have just 1.45 million (1.07%) recorded votes?

Richard Charnin
Aug.4, 2019

National Exit Poll (matched to the bogus recorded vote)
Party ID: 36Dem, 33Rep, 31Ind
Trump had 88% of Reps and 8% of Dems
Trump had 46% of Independents; Clinton 42%
Stein had 1% of Dems, 3% of Independents and 1.45 million (1.07%) votes
Clinton wins by 2.83 million (48.25-46.17%)

Estimated True Vote adjustments
Party ID: 32Dem, 28Rep, 40Ind (Gallup Voter affiliation survey)
Trump had 91% of Rep and 11% of Dems
Trump had 50% of Independents; Clinton 38%
Stein had 4% of Dems, 6% of Independents and 5.2 million (3.82%) votes
Trump wins by 7.57 million (49.00-43.44%)

Summary (approximate)
Trump had 3.9 million more votes than recorded
Stein had 3.7 million more votes than recorded
Clinton had 6.5 million fewer votes than recorded

Sensitivity Analysis
25 Scenarios of Trump shares of Republicans and Independents
In the worst case scenario, he has 46% of Independents and 89% of Republicans.
He still wins by 1.7 million votes.

Note: McMullin had 0.72 million and Others  had 0.96 million recorded votes

			National Exit Poll
	Party-ID	Clinton	Trump	Johnson	Stein
Dem	36%	89.0%	8%	1%	1%
Rep	33%	8.0%	88%	3%	0%
Ind	31%	42.0%	46%	6%	3%
Calc	100.0%	47.70%	46.18%	3.21%	1.29%
Votes	136.217	64.98	62.91	4.37	1.76
Recorded	100.0%	48.25%	46.17%	3.29%	1.07%
Votes	136.218	65.72	62.89	4.48	1.45
Change	-0.001	-0.74	0.02	-0.11	0.30
	Margin	2.83
	Gallup	Adjusted	National True Vote
	Party-ID	Clinton	Trump	Johnson	Stein
Dem	32%	83.0%	11%	1%	4%
Rep	28%	6.0%	91%	2%	0.5%
Ind	40%	38.0%	50%	5%	5%
Calc	100.0%	43.44%	49.00%	2.88%	3.42%
Votes	136.217	59.17	66.75	3.92	4.66
Recorded	100.0%	48.25%	46.17%	3.29%	1.07%
Votes	136.218	65.72	62.89	4.48	1.45
Change	-0.001	-6.55	3.86	-0.56	3.20
		Margin	7.57

 

Sensitivity Analysis

			Trump % Rep
Trump	89.0%	90.0%	91.0%	92.0%	93.0%
% Ind			Trump
50.0%	48.4%	48.7%	49.0%	49.3%	49.6%
49.0%	48.0%	48.3%	48.6%	48.9%	49.2%
48.0%	47.6%	47.9%	48.2%	48.5%	48.8%
47.0%	47.2%	47.5%	47.8%	48.1%	48.4%
46.0%	46.8%	47.1%	47.4%	47.7%	48.0%
			Clinton
50.0%	44.0%	43.7%	43.4%	43.2%	42.9%
49.0%	44.4%	44.1%	43.8%	43.6%	43.3%
48.0%	44.8%	44.5%	44.2%	44.0%	43.7%
47.0%	45.2%	44.9%	44.6%	44.4%	44.1%
46.0%	45.6%	45.3%	45.0%	44.8%	44.5%
			Vote Share Margin
50.0%	4.4%	5.0%	5.6%	6.1%	6.7%
49.0%	3.6%	4.2%	4.8%	5.3%	5.9%
48.0%	2.8%	3.4%	4.0%	4.5%	5.1%
47.0%	2.0%	2.6%	3.2%	3.7%	4.3%
46.0%	1.2%	1.8%	2.4%	2.9%	3.5%
			Trump Votes (mil)
50.0%	66.0	66.4	66.75	67.1	67.5
49.0%	65.4	65.8	66.20	66.6	67.0
48.0%	64.9	65.3	65.66	66.0	66.4
47.0%	64.3	64.7	65.11	65.5	65.9
46.0%	63.8	64.2	64.57	64.9	65.3
			Clinton Votes (mil)
50.0%	59.9	59.6	59.17	58.8	58.4
49.0%	60.5	60.1	59.72	59.3	59.0
48.0%	61.0	60.6	60.26	59.9	59.5
47.0%	61.6	61.2	60.81	60.4	60.0
46.0%	62.1	61.7	61.35	61.0	60.6
			Vote Margin (mil)
50.0%	6.0	6.8	7.57	8.3	9.1
49.0%	5.0	5.7	6.48	7.2	8.0
48.0%	3.9	4.6	5.39	6.2	6.9
47.0%	2.8	3.5	4.30	5.1	5.8
46.0%	1.7	2.5	3.21	4.0	4.7

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1258479551

 

 

 

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10 ways that Big Tech companies could shift millions of votes in the 2018 Midterms and the Power of Search Engines to Influence Votes and Opinions

Richard Charnin
July 20, 2019

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10 ways that Big Tech companies could shift millions of votes in the 2018 Midterms and the Power of Search Engines to Influence Votes and Opinions

Professor Robert Epstein wrote this before the 2018 midterms: “Here are 10 ways—seven of which I am actively studying and quantifying—that Big Tech companies could use to shift millions of votes this coming November with no one the wiser”.

“And what if the tech giants are all leaning in the same political direction? What if the combined weight of their subtle and untraceable manipulative power favors one political party? If 90 million people vote this November in the United States, with, perhaps, a third undecided at some point in time (that’s 30 million people), I estimate that the combined weight of Big Tech manipulations could easily shift upwards of 12 million votes without anyone knowing. That’s enough votes to determine the outcomes of hundreds of close local, state, and congressional races throughout the country, which makes the free-and-fair election little more than an illusion”.

https://www.theepochtimes.com/10-ways-big-tech-can-shift-millions-of-votes-in-the-november-elections-without-anyone-knowing_2671195.html

Manipulating Minds: The Power of Search Engines to Influence Votes and Opinions
Robert Epstein PhD
“Research directed by the author since 2013 suggests that such an elite now exists: that a small group of corporate executives now has the power to shift opinions, purchases, and even the outcomes of elections on a massive scale around the world without anyone being the wiser. That this power exists is now beyond question; perhaps more troubling is the growing number of indications such power is actually being wielded”.

https://aibrt.org/downloads/EPSTEIN_2018-Manipulating_minds-The-power_of_search_engines_to_influence_votes_and_opinions-UNCORRECTED_PROOFS.pdf

 

Big Tech Massive Influence on 2016 Election

Richard Charnin
7/20/19

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Big Tech Massive Influence on 2016 Election

Dr. Robert Epstein exposes Google’s role in America’s elections. His analysis indicates that from 2.6 to 10.4 million votes were shifted to Clinton in the 2016 election by using search engine manipulation and other techniques.

Epstein has been a Research Psychologist for 30 years, He received his PhD from Harvard. His focus has been on Google and its ability to manipulate the thinking of people. Google’s search algorithm supported Clinton in 2016. In 2020, up to 15 million votes could be shifted.

Epstein is working on a system to counter Big Tech. He states that Congress needs to end the Google monopoly by declaring its database to be public.

https://www.c-span.org/video/?c4808552/big-tech-massive-influence-elections

https://www.theepochtimes.com/10-ways-big-tech-can-shift-millions-of-votes-in-the-november-elections-without-anyone-knowing_2671195.html?fbclid=IwAR09Kw0f3WCWCFglba1pmW8JNMzSZ2zzFspfwbL1n3TPKBBaULmhtKiy_zU

https://www.usatoday.com/story/opinion/2018/09/13/google-big-tech-bias-hurts-democracy-not-just-conservatives-column/1265020002/

https://www.businessinsider.com/google-influence-on-2016-election-2015-8

https://richardcharnin.wordpress.com/2018/05/01/the-myth-hrc-fbi-doj-deep-state-thought-clinton-would-win-easily/

 

CrowdStrikeOut: Mueller’s Own Report Undercuts Its Core Russia-Meddling Claims

CrowdStrikeOut: Mueller’s Own Report Undercuts Its Core Russia-Meddling Claims

Richard Charnin
July 16, 2019

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I copied the author’s summary of the article’s main points. I did not write it. Maté did an awesome job. In my opinion, this is the best analysis ever written on the biased Mueller Report. The points should be the basis for questions to Mueller when he testifies. No wonder the Dems are scared.

By Aaron Maté, RealClearInvestigations
https://www.realclearinvestigations.com/articles/2019/07/05/crowdstrikeout_muellers_own_report_undercuts_its_core_russia-meddling_claims.html

While the 448-page Mueller report found no conspiracy between Donald Trump’s campaign and Russia, it offered voluminous details to support the sweeping conclusion that the Kremlin worked to secure Trump’s victory. The report claims that the interference operation occurred “principally” on two fronts: Russian military intelligence officers hacked and leaked embarrassing Democratic Party documents, and a government-linked troll farm orchestrated a sophisticated and far-reaching social media campaign that denigrated Hillary Clinton and promoted Trump.

But a close examination of the report shows that none of those headline assertions are supported by the report’s evidence or other publicly available sources. They are further undercut by investigative shortcomings and the conflicts of interest of key players involved:

1-The report uses qualified and vague language to describe key events, indicating that Mueller and his investigators do not actually know for certain whether Russian intelligence officers stole Democratic Party emails, or how those emails were transferred to WikiLeaks.

2- The report’s timeline of events appears to defy logic. According to its narrative, WikiLeaks founder Julian Assange announced the publication of Democratic Party emails not only before he received the documents but before he even communicated with the source that provided them.

3- There is strong reason to doubt Mueller’s suggestion that an alleged Russian cutout called Guccifer 2.0 supplied the stolen emails to Assange.

4- Mueller’s decision not to interview Assange – a central figure who claims Russia was not behind the hack – suggests an unwillingness to explore avenues of evidence on fundamental questions.

5- U.S. intelligence officials cannot make definitive conclusions about the hacking of the Democratic National Committee computer servers because they did not analyze those servers themselves. Instead, they relied on the forensics of CrowdStrike, a private contractor for the DNC that was not a neutral party, much as “Russian dossier” compiler Christopher Steele, also a DNC contractor, was not a neutral party. This puts two Democrat-hired contractors squarely behind underlying allegations in the affair – a key circumstance that Mueller ignores.

6- Further, the government allowed CrowdStrike and the Democratic Party’s legal counsel to submit redacted records, meaning CrowdStrike and not the government decided what could be revealed or not regarding evidence of hacking.

7- Mueller’s report conspicuously does not allege that the Russian government carried out the social media campaign. Instead it blames, as Mueller said in his closing remarks, “a private Russian entity” known as the Internet Research Agency (IRA).

8- Mueller also falls far short of proving that the Russian social campaign was sophisticated, or even more than minimally related to the 2016 election. As with the collusion and Russian hacking allegations, Democratic officials had a central and overlooked hand in generating the alarm about Russian social media activity.

9- John Brennan, then director of the CIA, played a seminal and overlooked role in all facets of what became Mueller’s investigation: the suspicions that triggered the initial collusion probe; the allegations of Russian interference; and the intelligence assessment that purported to validate the interference allegations that Brennan himself helped generate. Yet Brennan has since revealed himself to be, like CrowdStrike and Steele, hardly a neutral party — in fact a partisan with a deep animus toward Trump.

Much more at link….

 

My first job was Mathematician/ Numerical Control Engineer for Grumman Aerospace Corp

Richard Charnin
June 17, 2019

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I can’t believe it’s been 50 years since Apollo 11 landed on the moon. In 1965, my first job was as a Mathematician/ Numerical Control Engineer for Grumman Aerospace Corp (GAC) which built the Lunar Module. GAC was just five minutes from my home.

In programming automated machine tools to build naval and commercial aircraft parts, I often visited the manufacturing plant to see my work in progress. It was a very exciting time working with a great group of enginners.

The NC programs were written for an IBM 7094 mainframe computer running APT(Automatic Programmed Tools) a large Fortran-based system. The 7094 took up 3000 sq feet of floor space in the engineering building. It had just 512K of RAM- less than a tablet today.

It’s amazing that primitive 1969 computer technology could achieve the moon landing. The following article by Scott Davis addresses and debunks some of the common arguments behind the Moon landing conspiracy theories.
https://spacecentre.co.uk/blog-post/know-moon-landing-really-happened/

It contains explanations of…
– Van Allen Belt Radiation
– Flag flapping on the moon
– No stars?
– Strange shadows
– Moon rock prop

Other evidence:
– Apollo 15 site past and present
– Footprints
– Moon rocks

 

Quinnipiac vs. Rasmussen: Trump vs. Biden approval ratings and national poll

Richard Charnin
June 14, 2019

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It is way too early to consider presidential polls. But this analysis shows that the Quinnipiac Univ.  poll of Biden  leading Trump by 13% is implausible. We consider the 2016 race demographic and party-ID (Census, Gallup, Quinnipiac).

Quinnipac polled Registered voters. Rasmussen polled Likely Voters.

Trump’s approval ratings match his projected vote shares.
Rasmussen (LV): Trump leads 51-47%; (Census (Race) and Gallup (party ID)
Quinnipiac (RV): Biden leads 53-40%; (Census (Race) and Quinipiac (party ID)

Rasmussen: Trump leads whites by 61-37%.
Quinnipiac: Trump leads whites by just 47-46%.
Note Trump won whites by 57-37% in 2016.

Rasmussen: Trump leads Independents by 51-46%.
Quinnipiac: Biden leads by 56-28%.
Trump won Independents by 48-42% in 2016.

https://www.realclearpolitics.com/epolls/other/president_trump_job_approval-6179.html?utm_campaign=distroscale&utm_medium=video-player&utm_source=polls

Rasmussen	Sample (LV)	Census	Biden	Trump
White	1100	73.3%	37%	61%
Black	186	12.4%	87%	12%
Hispanic,Other	215	14.3%	63%	33%
Total	1500	100.0%	46.9%	50.9%
Rasmussen		Gallup
Dem	465	31%	88%	11%
Rep	450	30%	6%	93%
Ind	565	39%	46%	51%
Total	1500	100.0%	47.0%	51.2%
Quinnipiac	Sample (RV)	Party-ID	Biden	Trump
Dem-actual	503	41.4%	95%	3%
Rep-est	470	38.7%	6%	91%
Ind-est	241	19.8%	56%	28%
Total – actual	1214	100.0%	52.8%	42.0%
Quinnipiac		Census
White	890	73.3%	46%	47%
Black	151	12.4%	85%	12%
Hispanic,Other	174	14.3%	58%	33%
Total	1214	100.0%	52.6%	40.7%

This is why you should never trust MSM pollsters.

https://www.realclearpolitics.com/epolls/other/president_trump_job_approval-6179.html?utm_campaign=distroscale&utm_medium=video-player&utm_source=polls

Poll	Date	Sample	Approve	Disapprove	Spread
MSM
Reuters/Ipsos	6/10 – 6/11	983 RV	41	58	-17
Economist/YouGov	6/9 – 6/11	1107 RV	45	52	-7
Quinnipiac	6/6 – 6/10	1214 RV	42	53	-11
Politico/Morning Consult	6/7 – 6/9	1991 RV	41	56	-15
The Hill/HarrisX	6/7 – 6/8	1001 RV	45	55	-10
NPR/PBS/Marist	5/31 – 6/4	783 RV	43	49	-6
IBD/TIPP	5/30 – 6/7	906 A	42	52	-10
CNN	5/28-5/31	902 RV	40	53	-13
Average			42.57	52.86	-10.29
Non-MSM
Rasmussen Reports	6/11 – 6/13	1500 LV	51	47	4
Harvard-Harris	5/29 – 5/30	1295 RV	48	52	-4
Zogby Analytics	5/2-5/9	852 LV	51	48	3
Average			50.00	49.00	1.00

In the CNN sample, 34% described themselves as Democrats, 27% as Republicans, 39% as Independents or members of another party;   86% of Republicans, 7% of Democrats and 44% of Independents approve of Trump. Total approval is 42.8%.

Trump approval is calculated for independent pollsters using Gallup Party ID: Dem 31%, Ind 38%, Rep 30%. Estimated Trump  approval is 93% Repub, 12% Dem and 46% Independent. Total approval is 49.6%.

Party-ID	Gallup	Trump	CNN	Trump
Dem	31%	12%	34%	7%
Rep	30%	93%	27%	86%
Ind	38%	46%	39%	44%
Total Approval	100%	49.6%	100%	42.8%

https://thehill.com/homenews/campaign/447972-biden-leads-trump-by-landslide-proportions-in-new-national-poll

http://www.cnn.com/election/results/exit-polls/national/president

http://www.gallup.com/poll/15370/party-affiliation.aspx

http://www.rasmussenreports.com/public_content/politics/trump_administration/trump_approval_index_history

 

TRUMP WON THE TRUE POPULAR VOTE

Richard Charnin
May 10, 2019

Buy this book! Look inside. It is the only one which does a complete mathematical analysis of the 2016 election. Don’t believe the media/DNC/pundit propaganda that Hillary won by 2.8 million votes.

https://www.amazon.com/Trump-Won-True-Vote-Independents/dp/1979900973/ref=sr_1_2?s=books&ie=UTF8&qid=1512494633&sr=1-2&refinements=p_27%3ARichard+Charnin

TRUMP WON THE TRUE POPULAR VOTE.

Track record: I exactly forecast the BOGUS recorded electoral vote and estimated the True Vote in each of the last three elections.

IT’S ABOUT TIME TO EXPOSE THE HRC POPULAR VOTE MYTH WHICH IS THE BASIS FOR SPYGATE.

https://richardcharnin.wordpress.com/2016/11/07/2016-election-model-forecast/

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