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Ohio: New Quinnipiac poll shows Trump behind by 4 points

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

Ohio is traditionally a battleground state, where the Republican and Democratic candidates have often achieved similar voter support. This is the reason why the election outcome here is considered important in determining who will win the majority of electoral votes.

Quinnipiac poll results
49

Clinton

45

Trump

The results show that 49.0% of respondents indicated that they would vote for former Secretary of State Hillary Clinton, whereas 45.0% indicated that they would vote for businessman Donald Trump.

The poll was conducted from July 30 to August 7. A total of 812 likely voters responded. The margin of error is +/-3.4 points. This means that the levels of voter support for the Democratic and the Republican candidate do not differ significantly.

Putting the results in context

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

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

Comparison to other polls

If we look at an average of Ohio polls, Clinton's current two-party vote share is at 51.5%. This value is 0.6 percentage points lower than her corresponding numbers in the Quinnipiac poll. This difference is within the poll's sampling error, which means that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote foresees Clinton to gain 51.0% of the two-party vote in Ohio. That is, Polly's combined forecast is 1.1 points below her polling numbers. Again, a look at the poll's error margin 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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