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North Carolina: Virtual tie between Trump and Clinton in latest High Point*High Point* poll

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Results of a new poll carried out by High PointHigh Point were circulated. The poll asked interviewees from North Carolina for whom they will vote: Donald·Trump or Hillary·Clinton.

High PointHigh Point poll results
43

Clinton

42

Trump

The results show that 43.0% of respondents said that they would vote for former First Lady Hillary Clinton, whereas 42.0% are going to vote for businessman Donald Trump.

The poll was conducted from September 17 to September 22. A total of 404 likely voters responded. The sampling error is +/-4.9 percentage points, which means that the poll results for the candidates of both parties do not differ significantly.

Putting the results in context

As any other method, polls are subject to bias. Hence, you should not have too much confidence in the results of a single poll. Rather than relying on results from single polls, the best practice scientific advice is to use combined polls or, even better, a combined forecast that relies on forecasts from different methods, each of which draws upon different data.

For the following comparison, we translate Clinton's and Trump's raw poll numbers into shares of the two-party vote. This yields figures of 50.6% for Clinton and 49.4% for Trump.

Results compared to other polls

Looking at an average of North Carolina polls, Clinton's current two-party vote share is at 49.6%. Compared to his numbers in the High PointHigh Point poll Clinton's poll average is 1.1 percentage points worse. This margin is within the poll's margin of error, which means that the poll is not an outlier.

The poll compared with PollyVote's forecast

The most recent PollyVote expects Clinton to gain 49.1% of the two-party vote in North Carolina. Hence, Polly's combined forecast is 1.5 points below his polling numbers. The PollyVote forecast is thus within the poll's sampling 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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