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Pennsylvania: Virtual tie between Trump and Clinton in latest Emerson*Emerson* poll

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Results of a new poll conducted by EmersonEmerson were distributed. The poll asked interviewees from Pennsylvania for whom they will vote: Democrat Hillary Clinton or Republican Donald Trump.

EmersonEmerson poll results
46

Clinton

43

Trump

Of those who responded, 46.0% said that they plan to vote for former New York Senator Hillary Clinton, whereas 43.0% said that they would give their vote to real estate developer Donald Trump.

The poll was in the field between August 25 and August 28. The sample size was 800 likely voters. If one takes into account the poll's margin of error of +/-3.4 percentage points, the results reflect a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. As a result, one should not rely too much on the results of an individual poll. Instead of trusting the results from single polls, we recommend to use combined polls or, even better, the combined PollyVote forecast that draws upon forecasts from different methods, each of which draws upon different data.

In order to make the results comparable to forecasts from benchmark methods, you can convert them into two-party vote shares. This yields figures of 51.7% for Clinton and 48.3% for Trump.

Comparison to other polls

If we look at an average of Pennsylvania polls, Clinton's two-party vote share is currently at 53.8%. Compared to her numbers in the EmersonEmerson poll Clinton's poll average is 2.1 percentage points better. This difference is within the poll's error margin, which means that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The current PollyVote predicts Clinton to gain 54.2% of the two-party vote in Pennsylvania. Hence, the PollyVote forecast is 2.5 points above her polling numbers. The PollyVote forecast is therefore within the poll's error margin.

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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