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Iowa: Trump with slight advantage in new Emerson poll

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

Historically, Iowa has been a purple state, in which neither the Democrats nor the Republicans have had overwhelming support to secure that state's electoral college votes. This is the reason why forecasts in this state are of particular value.

Emerson poll results
39

Clinton

44

Trump

The results show that 39.0% of interviewees indicated that they would cast a ballot for former New York Senator Hillary Clinton, while 44.0% are going to vote for businessman Donald Trump.

The poll was conducted from August 31 to September 1 among 600 likely voters. Taking into account the poll's error margin of +/-3.9 percentage points, the results reflect a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. In general, one should not put too much trust in the results of a single poll. Rather than trusting the results from single polls, the recommended strategy rely on combined polls or, even better, the combined PollyVote forecast that draws upon forecasts from different methods, each of which draws upon different data.

For the following comparison, we convert the candidates' raw poll numbers into two-party vote shares. The respective figures are 47.0% for Clinton and 53.0% for Trump.

Results vs. other polls

Looking at an average of Iowa polls, Trump's two-party vote share is currently at 50.5%. This value is 2.5 percentage points lower than her respective numbers in the Emerson poll. This difference is within the poll's sampling error, which suggests that the poll is not an outlier.

Results compared to the combined PollyVote forecast

The most recent PollyVote expects Trump to gain 48.4% of the two-party vote in Iowa. Hence, Polly's forecast is 4.6 points below her polling numbers. Again, a look at the poll's sampling error reveals that this deviation is significant.

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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