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Iowa: Clinton tied with Trump in latest Loras poll


Loras published the results of a new poll. In this poll, respondents from Iowa were asked for whom they will vote: Hillary Clinton or Donald Trump.

In Iowa, the election outcome is usually close. This is why the state is commonly referred to as a purple state, which makes it particularly interesting from a forecasting perspective.

Loras poll results




According to the results, real estate developer Donald Trump and former New York Senator Hillary Clinton have identical levels of support, each with 42.0% of the vote.

The poll was carried out from September 20 to September 22 among 491 likely voters. If one accounts for the poll's error margin of +/-4.4 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, as they may contain 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 other methods, we translate them into shares of the two-party vote. The results of the actual poll mean 50.0 % for Clinton and 50.0 % for Trump in the two-party vote share.

Comparison to other polls

An average of recent polls in Iowa has Clinton at 48.1% of the two-party vote. When compared to the average forecast of other polls Clinton performed 1.9 percentage points better in the poll. This difference is outside the poll's error margin, which suggests that the poll is an outlier.

The poll compared with PollyVote's prediction

The most recent PollyVote predicts Clinton to gain 50.4% and Trump 49.7% of the two-party vote in Iowa. Clinton has 0.4 percentage points less when the results of the poll are compared to the combined PollyVote forecast for Iowa. The PollyVote forecast is thus outside 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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