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Iowa: New Quinnipiac poll has Clinton trailing by 6 points

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Results of a new poll carried out by Quinnipiac were published on October 9. The poll asked interviewees from Iowa for whom they will vote: Hillary Clinton or Donald Trump.

Iowa is traditionally a swing state, where the candidates of both major parties have historically achieved similar voter support. Hence, the election outcome here is considered crucial in determining who will win the majority of electoral votes.

Quinnipiac poll results
44

Clinton

50

Trump

The results show that 44.0% of respondents plan to give their vote to former First Lady Hillary Clinton, while 50.0% are going to vote for billionaire Donald Trump.

The poll was carried out from September 13 to September 21 with 612 likely voters. If one takes into account the poll's sampling error of +/-4.0 percentage points, the results reflect a statistical tie.

Putting the results in context

As a general rule, however, don't have too much faith in the results of single polls, since they can incorporate large errors. Rather, one should check how a poll's results compare to benchmark forecasts.

In order to make the results comparable to forecasts from benchmark methods, we translate them into two-party vote shares. This yields figures of 46.8% for Clinton and 53.2% for Trump.

Results compared to other polls

Looking at an average of Iowa polls, Trump's current two-party vote share is at 51.9%. Relative to her numbers in the Quinnipiac poll Trump's poll average is 1.3 percentage points worse. This deviation is within the poll's margin of error, which means that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The current PollyVote anticipates Trump to gain 49.5% of the two-party vote in Iowa. Hence, the PollyVote is 3.7 points below her polling numbers. Again, a look at the poll's margin of error shows that this deviation 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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