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New Quinnipiac poll in Pennsylvania: Clinton holds significant advantage

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

Quinnipiac poll results
52

Clinton

42

Trump

The results show that 52.0% of interviewees indicated that they would vote for former Secretary of State Hillary Clinton, while 42.0% would vote for billionaire Donald Trump.

The poll was conducted between July 30 and August 7. The sample size was 815 likely voters. There is a sampling error of +/-3.4 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

Single polls should be interpreted with caution, since they can include substantial errors. Rather than relying on results from single polls, you should use combined polls or, even better, a combined forecast that incorporates forecasts from different methods, each of which draws upon different data.

For the following comparison, we convert Trump's and Clinton's raw poll numbers into two-party vote shares. The respective figures are 55.3% for Clinton and 44.7% for Trump. In the most recent Quinnipiac poll on August 20 Clinton received only 44.7%, while Trump received only 0.0%.

Results compared to other polls

Clinton currently runs at 55.1% of the two-party vote according to an average of recent polls in Pennsylvania. This value is 0.2 percentage points lower than her respective numbers in the Quinnipiac poll. This margin is within the poll's sampling error, which suggests that the poll is not an outlier.

The poll in comparison with PollyVote's forecast

The latest PollyVote expects Clinton to gain 54.6% of the two-party vote in Pennsylvania. Hence, the PollyVote forecast is 0.7 points below her polling numbers. Again, a look at the poll's error margin 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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