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Clinton leads in Pennsylvania by 10 points in new Susquehanna poll

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

Susquehanna poll results
47

Clinton

37

Trump

Of those who answered the question, 47.0% said that they intend to vote for former First Lady Hillary Clinton, whereas 37.0% declared that they would give their vote to billionaire Donald Trump.

The poll was conducted from July 31 to August 4 among 772 likely voters. The sampling error is +/-3.5 percentage points, which means that the levels of voter support for both parties' candidates differ significantly.

Putting the results in context

As any other method, polls are subject to bias. Hence, you should not put too much trust in the results of an individual poll. Rather than relying on results from single polls, the best practice scientific advice is to look at combined polls or, even better, the combined PollyVote forecast that incorporates forecasts from different methods, each of which draws upon different data.

In order to make the results comparable to forecasts from benchmark methods, one can convert them into two-party vote shares. This procedure results in values of 56.0% for Clinton and 44.1% for Trump.

Comparison to other polls

If we look at an average of Pennsylvania polls, Clinton's current two-party vote share is at 55.2%. This value is 0.8 percentage points lower than her respective numbers in the Susquehanna poll. This difference is within the poll's sampling error, which means that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The current PollyVote expects Clinton to gain 54.6% of the two-party vote in Pennsylvania. Hence, Polly's forecast is 1.4 points below her polling numbers. Again, a look at the poll's sampling error suggests 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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