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Clinton holds solid advantage in new GQR (D-Democracy Corps) poll


Results of a new national poll administered by GQR (D-Democracy Corps) were released. The poll asked interviewees for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

GQR (D-Democracy Corps) poll results




Of those who responded, 53.0% said that they would vote for former Secretary of State Hillary Clinton, while 41.0% indicated that they would give their vote to billionaire Donald Trump.

The phone poll was carried out from October 21 to October 24 with 900 likely voters. Considering the poll's sampling error of +/-3.3 percentage points, the spread between both candidates is statistically significant.

Putting the results in context

Individual polls should be interpreted with caution, as they often incorporate large biases. Rather than relying on results from single polls, one should use combined polls or, even better, a combined forecast that uses forecasts from different methods, each of which uses different data.

For the following comparison, we convert the candidates' raw poll numbers into shares of the two-party vote. The respective figures are 56.4% for Clinton and 43.6% for Trump. For comparison: Only 53.8% was gained by Clinton in the GQR (D-Democracy Corps) poll on July 18, for Trump this result was 46.2%.

Comparison to other polls

An average of recent polls has Clinton at 53.5% of the two-party vote. This value is 2.9 percentage points lower than respective numbers in the GQR (D-Democracy Corps) poll. This difference is within the poll's error margin, which means that the poll is not an outlier.

The poll compared with PollyVote's prediction

The most recent PollyVote anticipates Clinton to gain 54.1% of the two-party vote. This means that the PollyVote forecast is 2.3 points below polling numbers. Again, a look at the poll's sampling error reveals that this difference is negligible.

This article was automatically generated by the PollyBot, which uses algorithms developed by AX Semantics to generate text from data stored in our API. The exact dataset underlying this particular article can be found here.

Please let us know if you find any typos, missing words, or grammatical errors. Your feedback helps us to further improve the quality of the texts.

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