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Pennsylvania: New Franklin & Marshall poll shows Clinton with 7 points lead

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

Franklin & Marshall poll results
47

Clinton

40

Trump

The results show that 47.0% of respondents are going to give their vote to former Secretary of State Hillary Clinton, whereas 40.0% are going to give their vote to billionaire Donald Trump.

This poll was conducted from August 25 to August 29, among a random sample of 496 likely voters. If one takes into account the poll's margin of error of +/-5.6 percentage points, the results reflect a statistical tie.

Putting the results in context

In general, however, you should not have too much faith in the results of single polls, as they sometimes incorporate large errors. Rather than relying on results from single polls, the best practice scientific advice is to consult combined polls or, even better, a combined forecast that draws upon different methods and data.

For the following analysis, we convert Trump's and Clinton's raw poll numbers into shares of the two-party vote. The resulting figures are 54.0% for Clinton and 46.0% for Trump.

Results in comparison to other polls

Looking at an average of Pennsylvania polls, Clinton's current two-party vote share is at 53.7%. This value is 0.3 percentage points lower than her respective numbers in the Franklin & Marshall poll. This margin is within the poll's sampling error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The most recent PollyVote expects Clinton to gain 54.1% of the two-party vote in Pennsylvania. Hence, Polly's prediction is 0.1 points above her 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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