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Ohio: Trump and Clinton virtually tied in new Quinnipiac poll


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

In Ohio, the popular vote is often decided by a narrow margin. This is why the state is commonly viewed as a swing state, which makes it particularly interesting from a forecasting perspective.

Quinnipiac poll results




Of those who answered the question, 45.0% said that they will vote for former New York Senator Hillary Clinton, whereas 46.0% revealed that they would give their vote to real estate developer Donald Trump.

The poll was conducted from August 29 to September 7 with 775 likely voters. Given the poll's sampling error of +/-3.5 percentage points, the results reflect a statistical tie.

Putting the results in context

Individual polls can include large biases, and should be treated with caution. Rather, one should check how a poll's results compare to benchmark forecasts.

For the following analysis, we translate Trump's and Clinton's raw poll numbers into shares of the two-party vote. The corresponding figures are 49.5% for Clinton and 50.6% for Trump. On August 7 Clinton received only 47.9% in the Quinnipiac poll and Trump received only 0.0%.

Results in comparison to other polls

If we look at an average of Ohio polls, Trump's current two-party vote share is at 50.6%. This value is 0 percentage points higher than her respective numbers in the Quinnipiac poll. This margin 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 most recent PollyVote anticipates Trump to gain 48.6% of the two-party vote in Ohio. Hence, Polly's prediction is 2.0 points below her polling numbers. Again, a look at the poll's error margin indicates that this difference 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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