Presidential Race Polls – Too many have zero validity

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It is about time the media stopped giving credence to small sample polls.

Why – Look at the fiasco of almost daily polling leading up to Brexit.

Recent history – Examining Polls leading up to Britain’s EU Referendum. All of the MSM presented small sample polls that seemed to confirm that the Government sponsored “Remain” result was comfortably leading BUT an online poll with a sample size of 907,000 indicated a 65% win for “Leave”.

Have a look @ The Daily Telegraph Article leading up to Brexit

These are the results of the almost 1 million sample sized Poll

The Daily Telegraph controlled mass Vote duplication by restricting voting to Digital Subscribers of this online Newspaper.

Now America has its own version that uses the largest possible data sample – The State voter registration data – Now an Analyst company with a web address – www.longroom.com produced a statistically valid proposition that the published Presidential Polls were biased.

Now, I found their claim interesting enough to examine more closely their methodology. BUT the site has now been taken down – no surprises here – you can, however, see the results of removing the bias from a wide number unprofessional pollsters – here

VoteforthePresidentOnline.com Online Interactive Poll

New Online Poll
Vote for the President Now (1 Vote per IP address)

Presidential Polls – Bias Analysis

rp_pw_wordpressRecently a Website – Longroom.com – provided comparison data of Presidential Pollsters has challenged the basis of these published Polls claiming a bias towards the Democrat Nominee.

The Methodology used by Longroom based on Voter registration data recorded in State voting districts is different from the many published Pollsters who rely on Sampling – by Phone / Interview / Digital sampling.

The accuracy of Political polls has become questionable over the last few years, first with the British General Elections and followed by significant lapses in accuracy in the lead up to the EU Referendum in Britain on June 23.

The Longroom data has been sorted by Polling company and this has shown significant aberration particularly concerning sampling variations within a single Pollster – For example – The 8 YouGov Polls all have varying samples (size and people). Rasmussen appears to be more consistent with the same sample size in each poll. Morning Consult has the greatest variation of Sample size.

Basically, there is no sound methodolgy for comparing polls even within a single polling company.

Using the Voter  Registration data as Longroom.com has done provides a validation methodology for assessing the accuracy of the various pollsters.

On 12 August, it appears that a Denial of Service operation has affected access to the Longroom.com site – this could be interpreted as suspicious.

The author of this page is a former Price Waterhouse Management Consultant and Statistician.

longroom_data

 

LongRoom Unbiased Poll
Trump 43.6%, Clinton, 42.8%
Trump leads by 0.6%

 

Donald J. Trump 43.4%  +0.6%
Hillary Clinton   42.8%

LongRoom Unbiased – Methodology

The LongRoom Polling Analysis uses the latest voting data from each state’s Secretary of State or Election Division. The voting data is kept current by incorporating the latest updates from each state as they become available. This means that the LongRoom Polling Analysis accurately reflects the actual voting demographics, precinct by precinct, county by county, and state by state.

Because the LongRoom Polling Analysis is exclusively data based, it makes it possible to demonstrate from the crosstabs of an individual poll whether that poll is either left or right leaning.

The analysis of the polls of each polling organization and the associated bias is illustrated in a line chart. The most recent poll results are displayed separately and a graphic representation of the amount the poll leans either left or right is shown.

The graphs below cover the last three presidential elections and show the LongRoom Polling Analysis of polls for those elections. In all cases, the LongRoom Analysis was accurate to within +/- 0.3%.

References for the voting data from each state are included below in the list of sources.

How do we know the polls are biased?

We know the polls are biased because the statisticians who produce the polls say they are biased, both explicitly and implicitly. This is also widely reported in the media. Let’s look at two recent examples. The Reuters/Ipsos poll last week, July 29th, decided to use “forcing” to assign those who were surveyed to a candidate, even if the person who was surveyed had no preference. Reuters/Ipsos applied this “technique” not only to their most recent poll, but went back through all their previous polls and redid them, assigning those with no preference to a candidate of the pollster’s choice. This innovative approach to polling was not universally popular with other pollsters, as Pat Caddell, a pollster with decades of experience, expounded in this article: “Pat Caddell on ‘Cooked’ Reuters Poll: ‘Never in My Life Have I Seen a News Organization Do Something So Dishonest’” . Another example would be the CNN poll from July 30th, where the crosstabs for Question P1 show that 97% of Democrats have committed to a candidate three months before the election. In the history of elections, it is difficult to find an example where 97% of a demographic have made up their minds on who to vote for even on election day, no less in the middle of summer before an election in November.

For a rather extensive list of biases that a statistician may introduce into a poll, there is an excellent article here by Nate Silver where he discusses the biases he uses in creating his analysis, and why he thinks his biases are good.

Statisticians also use “weighting” to produce the poll results that are published in the media. The weighting is simply how many of each demographic the statistician believes will vote based on the detailed questions that are asked when the poll is taken. An example of how this affects polls is demonstrated in the polls out this last week, ending July 31st. Some polls have changes of 10% and more in presidential preference while other polls have a change of only a few percent. Clearly, both of these results cannot be correct.

So like opinions, every statistician has their own biases, but none of them wants to see the other guy’s. Here at LongRoom we leave out the biases and let the data speak for itself.

How do you remove the bias in the polls?

As we discussed above, each poll reflects the biases of the statisticians who prepare the poll. Since each statistician has their own specific biases that they introduce into their poll, it is extremely difficult to compare one poll to another. At LongRoom we use the actual state voter registration data from the Secretary of State or Election Division of each state. We add no “expert” adjustments to the data. This means that all the polls are rationalized one to another based on actual data.

What can we expect going forward?

As the election approaches, the statisticians who produce the various polls will begin to back out their biases. In the final few weeks before the election, you will start to notice a convergence of all of the polls. This occurs because the statisticians will use essentially the same data that LongRoom is using now to produce their polls with their own biases removed. So, you might be thinking at this point, are you really saying that all of the polls will eventually match LongRoom? Yes, we are, it is a mathematical certainty, that as the election approaches, all of the polls will begin to match the polls here on LongRoom. This may be difficult for some to believe, however, there is an excellent archive at RCP that shows the poll results for the 2012 presidential election and this typical convergence of polls as the statisticians’ biases are backed out.

What is the earliest that you can tell who will be the next president?

The day after the election. This may sound humorous but it is actually the truth, there is no reliable predictor for who will win a democratic vote. An example of this is the March 14th, 2004 Spanish General Election which we covered and analyzed. On March 10th, 2004, the Conservative Party was leading in the polls, and as they were the incumbents, were likely to succeed in the election. However, on March 11th, there was a Madrid train bombing. The Conservative government quickly blamed the ETA Spanish Separatist group. As more information was uncovered, it became obvious that the bombing was the work of the Islamist group, Al-Queda. The Conservative government continued to claim it was ETA in spite of the mounting evidence. The electorate rapidly came to believe that the Conservative government was trying to cover up the Islamic involvement and gave the liberal opposition party a 5 point margin of victory. So, in a matter of only three days, there was an 8 point swing in voter preference.

For more information about the 2004 Spanish General Election and the impact the bombing had on it, Wikipedia has a write up here.

To make this example more relevant to our current presidential election, imagine that 3 days before the election there is a terrorist incident here in America, and Mr. Obama and Mrs. Clinton place the blame on right-wing Christian extremists, while Mr. Trump blames radical Islamic terrorists. As the hours tick by, it becomes obvious that the terrorist incident is the work of radical Islamic terrorists, however Mr. Obama and Mrs. Clinton continue to deny the Islamic involvement. Just as in Spain, it is game, set, match, and Mr. Trump is the next president of the United States.

So, if anyone pretends they can predict the election, just keep in mind: Life Happens.

What tools does LongRoom use?

We have developed our analytical model using the programming language that we and other actuaries have used for the last 30 years, APL.

Definition of Terrorism

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ISLAM CONDONES AND BREEDS TERRORISM

UK Government – Definition of Terrorism
September 2011

Outside the condition of a ‘declared war’

the use of action or threat of action, for the purpose of advancing a political, religious or ideological cause, which: –

a) involves serious violence against any person or property,

b) endangers the life of any person, or

c) creates a serious risk to the health or safety of the public or a section of the public.

 

NOW CONSIDER THE CHASM
BETWEEN THE PEOPLES OF ISLAM

Fifth Islamic Summit – Definition of Terrorism
Islam (Resolution 20/5-P (1.5) of the Fifth Islamic Summit) attempts to legitimize & differentiate as separate from terrorism:-

‘the struggle of peoples for their acknowledged national causes and the liberation of their territories. ‘

Summary Extract of Islamic Definition of Terrorism

We shall confirm that the definition of Terrorism does not apply to the following:

a. acts of national resistance exercised against occupying forces, colonizers and usurpers;
b. resistance of peoples against cliques imposed on them by the force of arms;
c. rejection of dictatorships and other forms of despotism and efforts to undermine their institutions;
d. resistance against racial discrimination and attacks on the latter’s strongholds;
e. retaliation against any aggression if there is no other alternative.

The above definition of Terrorism, however, does apply to the following:

a. acts of piracy on land, air and sea;

b. all colonialist operations including wars and military expeditions;
c. all dictatorial acts against peoples and all forms of protection of dictatorships, not to mention their imposition on nations;
d. all military methods contrary to human practice, such as the use of chemical weapons, the shelling of civilian populated areas, the blowing up of homes, the displacement of civilians, etc.;
e. all types of pollution of geographical, cultural and informational environment. Indeed, intellectual terrorism may be one of the most dangerous types of terrorism;
f. all moves that undermine adversely affect the condition of international or national economy, adversely affect the condition of the poor and the deprived, deepen up nations with the shackles of socioeconomic gaps, and chain up nations with the shackles of exorbitant debts;
g. all conspiratorial acts aimed at crushing the determination of nations for liberation and independence, and imposing disgraceful pacts on them.
The list of examples that fit in with the suggested definition is almost endless.

Islamic nations must make their position clear about whether they support:-

international law or
international terrorism

http://www.al-islam.org/al-tawhid/definition-terrorism.htm

Muslim Population in EU

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Source of Data – CIA World Factbook

Country Population Density – km2 Muslim Pop. % Total Population Muslim Population
France 114 9.00 66,030,000 5,942,700
Germany 229 3.70 80,620,000 2,982,940
United Kingdom 267 4.50 64,100,000 2,884,500
Spain 91 3.80 46,770,000 1,777,260
Bulgaria 66 14.00 7,265,000 1,017,100
Belgium 355 6.00 11,200,000 672,000
Netherlands 411 4.00 16,800,000 672,000
Italy 200 1.00 59,830,000 598,300
Sweden 21 5.00 9,593,000 479,650
Cyprus 87 33.00 1,140,000 376,200
Austria 100 4.20 8,474,000 355,908
Denmark 128 3.70 5,614,000 207,718
Greece 86 1.30 11,030,000 143,390
Romania 90 0.30 19,960,000 59,880
Finland 16 1.00 5,439,000 54,390
Croatia 79 1.20 4,253,000 51,036
Ireland 65 1.07 4,595,000 49,167
Slovenia 106 2.40 2,018,000 48,432
Portugal 115 0.30 10,460,000 31,380
Luxembourg 194 2.60 543,202 14,123
Slovakia 111 0.20 5,414,000 10,828
Czech Republic 134 0.10 10,520,000 10,520
Hungary 108 0.06 9,897,000 5,938
Malta 1322 1.00 423,282 4,233
Poland 122 0.05 38,530,000 20,000
Lithuania 47 0.01 2,956,000 296
Latvia 35 0.01 2,013,000 201
Estonia 29 0.01 1,325,000 133
506,812,484 18,454,075