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Clinton leads in Pennsylvania by 10 points in new Quinnipiac poll


Quinnipiac published the results of a new poll. In this poll, participants from Pennsylvania were asked for whom they will vote: Donald Trump or Hillary Clinton.

Quinnipiac poll results




Of those who replied, 52.0% said that they would vote for former New York Senator Hillary Clinton, whereas 42.0% indicated that they would give their vote to billionaire Donald Trump.

The poll was in the field between July 30 and August 7. The sample size was 815 likely voters. If one takes into account the poll's error margin of +/-3.4 percentage points, the gap between both candidates is statistically significant.

Putting the results in context

As any other method, polls are subject to bias. Thus, as a general rule, one should not have too much confidence in the results of a single poll. Rather than trusting the results from single polls, one should rely on combined polls or, even better, the combined PollyVote forecast that incorporates forecasts from different methods, each of which incorporates different data.

For the following comparison, we convert Clinton's and Trump's raw poll numbers into shares of the two-party vote. This yields figures of 55.3% for Clinton and 44.7% for Trump.

Results in comparison to other polls

Clinton currently achieves 54.5% of the two-party vote in an average of recent polls in Pennsylvania. In comparison to her numbers in the Quinnipiac poll Clinton's poll average is 0.8 percentage points worse. This margin is within the poll's margin of error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote predicts Clinton to gain 54.4% of the two-party vote in Pennsylvania. That is, Polly's prediction is 0.9 points below her polling numbers. Again, a look at the poll's sampling error suggests that this deviation is insignificant.

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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