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Ohio: Clinton with marginal lead in new Quinnipiac poll

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Results of a new poll administered by Quinnipiac were circulated. The poll asked respondents from Ohio for whom they will vote: Hillary Clinton or Donald Trump.

In Ohio, the election outcome is often close. Therefore, the state is commonly considered a battleground state, which makes it particularly interesting from a forecasting perspective.

Quinnipiac poll results
49

Clinton

45

Trump

Of those who answered the question, 49.0% said that they are going to vote for former Secretary of State Hillary Clinton, whereas 45.0% said that they would give their vote to real estate developer Donald Trump.

This poll was conducted from July 30 to August 7, among a random sample of 812 likely voters. If one accounts for the poll's sampling error of +/-3.4 percentage points, the results reflect a statistical tie.

Putting the results in context

Individual polls may contain large biases, which is why they should be interpreted with caution. Rather than trusting the results from single polls, the evidence-based approach is to use combined polls or, even better, the combined PollyVote forecast that uses forecasts from different methods, each of which draws upon different data.

To make the results comparable to forecasts from other methods, one can convert them into shares of the two-party vote. This procedure results in figures of 52.1% for Clinton and 47.9% for Trump.

Results in comparison to other polls

If we look at an average of Ohio polls, Clinton's current two-party vote share is at 52.2%. In comparison to her numbers in the Quinnipiac poll Clinton's poll average is 0.1 percentage points higher. This margin is within the poll's error margin, which means that the poll is not an outlier.

Results compared to the combined PollyVote forecast

The most recent PollyVote forecasts Clinton to gain 52.0% of the two-party vote in Ohio. Hence, Polly's combined forecast is 0.1 points below her polling numbers. The PollyVote forecast is therefore in line with 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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