APP - The Evidence Is Clear: Polls Are Not To Be Trusted

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Political polling season has arrived and serious minded people need to be wary. If you believe the coming election is important and you want to approach the election with a clear head, take polls with a grain of salt.

There’s a simple, unassailable truth about polls in the last election: they routinely surveyed more DEMOCRATS than Republicans, leading, I believe, to skewed results - a massive head fake that rippled through the markets.
I recommend that you not react to polls.

Or, better yet, see for yourself by finding the details of how each survey was conducted.

Here are a few examples of polls that garnered big headlines but that might just be inaccurate.

Last July 15th, headlines roared, “Trump trails Biden, Warren, and Sanders” citing a recent poll, but was this really the case?

Upon further investigation, the poll was comprised of 42% DEMOCRATS, 36% Republicans, 12% Independent, and 10% “other” or “not sure.”

The categories “other” and “not sure” were left undefined, but they almost certainly contributed to what appears to be a misrepresentation.

Recently, CNBC followed the same playbook, broadcasting headlines, “Trump Not Boosted by Strong American Economy."

They reached this conclusion from the results of a poll conducted by the Associated Press- National Opinions Research Center last June.

Respondents were asked if they approved of the overall job done by the president and if his tax cuts were benefiting them.

Only 39% of individuals approved of Trump and a measly 17% of people claimed they benefited from his tax policy.

Both of these figures are strikingly low, with 39% being the lowest average approval rating in decades.

Taking a closer look, the poll lacks accuracy at its core.

Out of 1,116 adults, 46% were DEMOCRATS, 36% were Republican and 44% were unemployed.

If a ten percentage point difference in the political party wasn't enough to facilitate a bias, 44% unemployment ought to do it.



https://www.forbes.com/sites/thomaslandstreet/2019/08/21/the-evidence-is-clear-polls-are-not-to-be-trusted/
 
Last August 13th, headlines blared about a Fox News poll ranking the DEMOCRATS and declaring that if the election was held today, Donald Trump would lose to each of the top three DEMOCRAT candidates.

This poll hit the mainstream news echo chamber for a week as the press fashioned any number of doomsday headlines (to which Donald Trump had to respond that he "was not happy with it").

Of course, that statement hit the news for another week.

Here, too, it appears that the results are skewed.

It turns out that Fox News polled 8% more DEMOCRATS than Republicans.

For proof of the distorting effects of such polling, just consider the Trump vs. Clinton race in 2016.

Out of twenty polls conducted by some of the most reputable news sources in the U.S., there was only one (IBD/TIPP) that gave Trump the edge on election day.

Most of these polls gave Clinton a 70% chance to win and some were 99% convinced.

Not surprisingly, CNBC published an article titled, “Trump Victory All but Impossible Based on Previous Races” a month before the election.

Obviously, CNBC was pretty far off the mark.

Again, attention to detail matters. In the research conducted in October 2016, 43% of the individuals interviewed were DEMOCRATS, 36% were Republicans, and 16% claimed to be Independent.

Based on their prediction and the real outcome of the election, it’s possible that seven percentage points is more than just a rounding error.
 
So, as the barrage of poll-driven headlines commences, take a moment, follow these easy instructions and see for yourselves if the story line created by pollsters is accurate.

If you look closely, you can find links embedded in or at the bottom of each article or perhaps below graphs, if provided.

Once you find the link to the source, you will be able to browse through the demographic and party affiliation data to make your own decision on its accuracy.

That way, you can have a sober viewpoint as the election unfolds.
 
One of the biggest mistakes that political analysts, especially those who spend a lot of time on Twitter, often make is they assume voters are as engaged in the process as they, or their audiences, are.

The reality is that, largely due to media fragmentation, the “average” (more accurately, “median”) voter is even less educated in comparison to us political junkies, who have never had more information instantly available than what we can easily *access today.

Consequently, at least half of the massive electorate for a presidential general election has been, whether we like it or not, paying very little, if any, attention to the race at this point.

Any information they have gleaned from all the media coverage of specifically the DEMOCRAT contest has been largely by accident, and their base of knowledge would be roughly that of what the least enthusiastic person at the Super Bowl party you attended possessed about the *Kansas City Chiefs.

This is why watching the DEMOCRAT race unfold is so incredibly amusing. It is obvious that DEMOCRATS are not equipped to think for themselves.

Part of the blame goes to a gutless and compromised news media that, for various reasons, had no self-interest in harshly vetting candidates like Bernie Sanders (he has a cult who will be pissed at them), Pete Buttigieg (he is gay and, therefore, it is not in the DNA of the liberal media to be able to criticize him), and Mike Bloomberg (he is still literally paying their salaries right now by spending millions in media *advertising).

But I mostly blame the pollsters who have been remarkably unimaginative and, frankly, overly politically-correct in their methods, which have provided voters with mostly meaningless and deceiving data.
 
Common problems with polls:

Improper sampling techniques

Samples should be random, otherwise poll results do not accurately represent the target population.

Biased questions

Questions framed to portray candidates or policies in a positive or negative light strongly influence responses.

Sample size

A survey is unlikely to turn up results consistent with the preferences of the entire population of the United States.

Sampling errors

The results from a sample don’t represent a population. This is called sampling error, and the likely size of the error is called the margin of error. If a poll reports that 53% of Americans prefer a candidate, but the margin of error is + or - 3%, you should not conclude that the majority of Americans prefer the candidate since the true percentage could be as little as 50%.
 
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