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Pennsylvania: 5 points lead for Clinton in latest Quinnipiac poll


Quinnipiac released the results of a new poll, in which respondents from Pennsylvania were asked for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

Quinnipiac poll results




Of those who answered the question, 48.0% said that they would vote for former Secretary of State Hillary Clinton, while 43.0% indicated that they would give their vote to billionaire Donald Trump.

The poll was carried out between August 29 and September 7. The sample size was 778 likely voters. There is a sampling error of +/-3.5 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

Individual polls should be regarded with caution, as they often include substantial errors. Instead of relying on results from single polls, forecasting research recommends to rely on combined polls or, even better, a combined forecast that relies on different methods and data.

In order to make the results comparable to benchmark forecasts, we translate them into shares of the two-party vote. This yields figures of 52.8% for Clinton and 47.3% for Trump. On September 1 Clinton received only 44.7% in the Quinnipiac poll and Trump received only 0.0%.

Results in comparison to other polls

If we look at an average of Pennsylvania polls, Clinton's two-party vote share is currently at 53.8%. In comparison to her numbers in the Quinnipiac poll Clinton's poll average is 1 percentage point better. This deviation is within the poll's sampling error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote expects Clinton to gain 54.1% of the two-party vote in Pennsylvania. Hence, the PollyVote is 1.3 points above her polling numbers. Again, a look at the poll's sampling error indicates 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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