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Latest CBS News/YouGov poll in Ohio: Trump trails by a slim margin

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CBS News/YouGov published the results of a new poll. In this poll, respondents from Ohio were asked for whom they will vote: Republican Donald Trump or Democrat Hillary Clinton.

In Ohio, the popular vote is usually close. This is the reason why the state is commonly considered a purple state, which makes it particularly interesting from a forecasting perspective.

CBS News/YouGov poll results
46

Clinton

40

Trump

Of those who answered the question, 46.0% said that they would vote for former Secretary of State Hillary Clinton, while 40.0% said that they would give their vote to billionaire Donald Trump.

The poll was conducted from August 17 to August 19. A total of 997 likely voters responded. There is a sampling error of +/-3.9 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. Thus, as a general rule, don't have too much confidence in the results of a single poll. At least, one should check how a poll's results compare to benchmark forecasts.

In order to make the results comparable to forecasts from benchmark methods, you can convert them into two-party vote shares. The respective figures are 53.5% for Clinton and 46.5% for Trump.

Results compared to other polls

If we look at an average of Ohio polls, Clinton's current two-party vote share is at 52.2%. Relative to her numbers in the CBS News/YouGov poll Clinton's poll average is 1.3 percentage points worse. This margin is within the poll's margin of error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The most recent PollyVote predicts Clinton to gain 52.0% of the two-party vote in Ohio. Hence, the PollyVote is 1.5 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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