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Monmouth poll in Pennsylvania: Trump trails by a significant margin

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Results of a new poll carried out by Monmouth were published. The poll asked participants from Pennsylvania for whom they will vote: Hillary Clinton or Donald Trump.

Monmouth poll results
50

Clinton

40

Trump

According to the results, 50.0% of interviewees will give their vote to former First Lady Hillary Clinton, while 40.0% would vote for billionaire Donald Trump.

The poll was conducted from September 30 to October 3 with 402 likely voters. Considering the poll's sampling error of +/-4.9 percentage points, the difference in voter support is statistically significant.

Putting the results in context

As any other method, polls are subject to bias. Hence, you should not focus too much on the results of a single poll. Instead of trusting the results from single polls, the evidence-based approach is to use combined polls or, even better, a combined forecast that uses forecasts from different methods, each of which draws upon different data.

For the following analysis, we convert the candidates' raw poll numbers into shares of the two-party vote. The corresponding figures are 55.6% for Clinton and 44.4% for Trump. To compare: Only 45.5% was gained by Clinton in the Monmouth poll on August 29, for Trump this number was only 0.0%.

Results vs. other polls

Clinton can currently count on 55.3% of the major two-party vote according to an average of recent polls in Pennsylvania. Relative to her numbers in the Monmouth poll Clinton's poll average is 0.3 percentage points worse. This difference is within the poll's error margin, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote foresees Clinton to gain 53.6% of the two-party vote in Pennsylvania. That is, the PollyVote is 2.0 points below her polling numbers. The PollyVote forecast is therefore in line with the poll's margin of error.

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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