Reuters Explains How It "Fudged" Its Polls

Over the past couple of weeks, we have constantly pointed out that polling data was seemingly being manipulated to "manufacture" artificial leads for the mainstream media's chosen candidate, Hillary Clinton.  By "oversampling" democrats and/or various minority groups, pollster after pollster kept rolling out predictions that seemed utterly ridiculous to us but were gobbled up by complicit media outlets.  Here is just a small sample of our headlines from the past couple of months:

"ABC/Wapo Effectively Admit To Poll Tampering As Hillary's "Lead" Shrinks To 2-Points"


"How Reuters "Tweaked" Its Latest Poll (Again) To Show A Clinton Lead"


"Statisticians Warn Of "Systemic Mainstream Misinformation" In Poll Data"


"CNN Goes "Full Reuters" - Attempts To Rig VP Debate Poll With Too Many Dems In Sample"


"New Podesta Email Exposes Playbook For Rigging Polls Through 'Oversamples'"

Not surprisingly, Reuters this morning officially confirmed everything we've been saying for the past several months about "oversamples" of certain demographic groups causing polling data to be artificially skewed toward Hillary.  As Reuters admits, "the models almost universally miscalculated how turnout was distributed among different demographic groups."

And that’s what happened Tuesday: The election models calculated the probabilities of a Clinton win that turned out to be high, because they viewed each state too much in isolation.


The Reuters/Ipsos States of the Nation project projected Clinton to win the popular vote 45 percent to 42 percent, and gave her a 90 percent probability of winning the 270 electoral votes needed to secure the election. In the end, Clinton won the popular vote by 47.7 percent to 47.5 percent, by the latest count, and Trump could win the Electoral College by as many as 303 votes to Clinton’s 233 when the tally is final.


The problem, said Cliff Young, president of Ipsos Public Affairs US, the polling partner of Reuters, came down to the models the pollsters used to predict who would vote - the so-called likely voters.


The models almost universally miscalculated how turnout was distributed among different demographic groups, Young said. And turnout was lower than expected, a result that generally favors Republican candidates.


Ultimately, missing that shift in the state polls tripped up the predictions. It also highlights how the otherwise empirical process of polling rests on a subjective foundation.


Each pollster must make a decision about turnout. Their decisions are informed by historical voting patterns. But the actual turnout in each state is unknowable before election day.

Trump Wins


As Reuters also notes, another flaw in the way the polls are presented is the overemphasis on the popular vote.  While the national polling data is a useful metric the more important determinant of presidential elections is the voter turnout estimates (i.e. "likely voters") in individual swing states.

Beyond the calculations of the candidates' odds of winning the Electoral College, there was a near constant stream so-called “horse race polls,” or tracker polls, that focused on the distribution of the national vote between the major candidates.


Here, too, pollsters -- and the media that co-sponsored or covered the polls -- stumbled, largely because the popular vote metric itself is of limited utility and cannot, of itself, predict the outcome of the Electoral College.


As of Wednesday morning, Clinton led the popular vote by slightly less than 1 percentage point. The McClatchy-Marist poll released on Nov. 3, for example, had Clinton up by one point - one of the most accurate calls of the popular vote. But even that headline number missed the point a bit, because she lost the election in the Electoral College.


A few polls correctly pegged Trump as the winner. The International Business Times/TIPP poll had Trump leading on Nov. 7. That poll put him ahead in the popular vote by two percentage points, which in the end overstated his share by about three points.


Young said both pollsters and journalist described the results of the national polls and predictions with a false precision by presenting the result as near absolutes.


“The forecasting models, which assign probabilities or chances to candidates, are no better than the polls themselves,” he said. “If the polls are off, the forecasting models will be off, too.”

Ironically, the one person who seemed to call this race better than anyone else was Michael Moore who called PA, OH, MI and WI all for Trump weeks ago.  Before November 8th all the "real" pollsters would have laughed at the idea of Trump winning all four of those states but that is, in fact, exactly what has happened.


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