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New Hampshire: 8 points lead for Clinton in new Emerson poll

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Emerson published the results of a new poll. In this poll, respondents from New Hampshire were asked for whom they will vote: Hillary Clinton or Donald Trump.

Historically, New Hampshire has been a swing state, in which neither the Republican Party nor the Democratic Party has had overwhelming support to clinch that state's electoral college votes. Hence, predictions here are of particular value.

Emerson poll results
44

Clinton

36

Trump

The results show that 44.0% of respondents indicated that they would vote for former Secretary of State Hillary Clinton, whereas 36.0% would vote for businessman Donald Trump.

This poll was conducted from October 17 to October 19, among a random sample of 900 likely voters. There is a sampling error of +/-3.2 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

Individual polls should be interpreted with caution, since they often contain large errors. At least, one should check how a poll's results compare to benchmark forecasts.

For the following analysis, we translate Clinton's and Trump's raw poll numbers into shares of the two-party vote. The resulting figures are 55.0% for Clinton and 45.0% for Trump.

Comparison to other polls

Looking at an average of New Hampshire polls, Clinton's two-party vote share is currently at 53.1%. Relative to her numbers in the Emerson poll Clinton's poll average is 1.9 percentage points worse. This difference is within the poll's sampling error, which suggests that the poll is not an outlier.

The poll compared with PollyVote's forecast

The current PollyVote forecasts Clinton to gain 52.9% of the two-party vote in New Hampshire. Hence, Polly's prediction is 2.1 points below her polling numbers. Again, a look at the poll's error margin suggests 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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