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Iowa: Clinton tied with Trump in new LorasLoras poll


Results of a new poll administered by LorasLoras were circulated. The poll asked participants from Iowa for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

Iowa is traditionally a battleground state, where the GOP and the Democrats have historically gained similar levels of voter support. Hence, the election outcome in that state is regarded important in determining the overall result of the presidential election.

LorasLoras poll results




According to the results, both candidates have the same level of support, each with 42.0% of the vote.

The poll was conducted from September 20 to September 22 among 491 likely voters. If one takes into account the poll's sampling error of +/-4.4 percentage points, the results reflect a statistical tie.

Putting the results in context

Individual polls can incorporate large errors, which is why they should be interpreted with caution. At the very least, one should check how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from other methods, you can convert 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

Clinton can currently count on 48.1% of the major two-party vote in an average of recent polls in Iowa. In comparison to the average forecast of other polls Clinton performed 1.9 percentage points better in the poll. This margin is outside the poll's error margin, which suggests that the poll is an outlier.

Comparison to the combined PollyVote

The most recent PollyVote predicts Clinton to gain 50.6% and Trump 49.5% of the two-party vote in Iowa. Clinton has 0.5 percentage points less when the results of the poll are compared to the combined PollyVote forecast for Iowa. Again, a look at the poll's error margin suggests 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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