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Pennsylvania: Big advantage for Clinton in Franklin & Marshall poll


Franklin & Marshall 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.

Franklin & Marshall poll results




According to the results, 49.0% of respondents intend to cast a ballot for former Secretary of State Hillary Clinton, while 38.0% intend to vote for real estate developer Donald Trump.

The poll was conducted from July 29 to August 2. A total of 389 likely voters responded. The error margin is +/-6.3 percentage points. This means that the levels of voter support for both parties' candidates do not differ significantly.

Putting the results in context

In general, however, you should not have too much faith in the results of single polls, because they may incorporate large errors. Rather than relying on results from single polls, forecasting research recommends to look at combined polls or, even better, the combined PollyVote forecast that relies on different methods and data.

For the following analysis, we convert Clinton's and Trump's raw poll numbers into shares of the two-party vote. This procedure yields values of 56.3% for Clinton and 43.7% for Trump.

Results in comparison to other polls

Clinton is currently at 55.1% of the two-party vote according to an average of recent polls in Pennsylvania. This value is 1.2 percentage points lower than her respective numbers in the Franklin & Marshall poll. This deviation is within the poll's sampling error, which means that the poll is not an outlier.

Results compared to the combined PollyVote forecast

The latest PollyVote predicts Clinton to gain 54.6% of the two-party vote in Pennsylvania. Hence, the combined PollyVote is 1.7 points below her polling numbers. Again, a look at the poll's error margin reveals 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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