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North Carolina: Trump and Clinton neck-and-neck in latest Suffolk University poll

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

Suffolk University poll results
41

Clinton

44

Trump

Of those who replied, 41.0% said that they will vote for former First Lady Hillary Clinton, while 44.0% revealed that they would give their vote to billionaire Donald Trump.

This poll was conducted from September 5 to September 7, among a random sample of 500 likely voters. There is a sampling error of +/-4.4 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

In general, however, don't have too much faith in the results of single polls, as they may contain large errors. Instead of trusting the results from single polls, forecasting research recommends to consult combined polls or, even better, a combined forecast that includes forecasts from different methods, each of which draws upon different data.

To make the results comparable to benchmark forecasts, we translate them into two-party vote shares. This procedure yields values of 48.2% for Clinton and 51.8% for Trump.

Comparison to other polls

Trump currently achieves 50.5% of the two-party vote in an average of recent polls in North Carolina. In comparison to his numbers in the Suffolk University poll Trump's poll average is 1.3 percentage points worse. This deviation is within the poll's margin of error, which suggests that the poll is not an outlier.

The poll in comparison with PollyVote's prediction

The most recent PollyVote predicts Trump to gain 50.9% of the two-party vote in North Carolina. This means that the PollyVote forecast is 0.9 points below his polling numbers. Again, a look at the poll's sampling error indicates that this deviation is insignificant.

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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