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Clinton leads in New Hampshire by 6 points in new UMass Lowell/7News poll


Results of a new poll carried out by UMass Lowell/7News were released. The poll asked interviewees from New Hampshire for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

New Hampshire is traditionally a battleground state, where the two major political parties have historically won similar levels of voter support. This is the reason why the election outcome here is viewed as important in determining the overall result of the presidential election.

UMass Lowell/7News poll results




The results show that 45.0% of interviewees will vote for former First Lady Hillary Clinton, whereas 39.0% are going to vote for businessman Donald Trump.

The poll was conducted from October 7 to October 11 with 517 likely voters. If one takes into account the poll's margin of error of +/-4.9 percentage points, the results reflect a statistical tie.

Putting the results in context

Single polls can include large errors, which is why they should be treated with caution. At the very least, one should check how a poll's results compare to benchmark forecasts.

To make the results comparable to benchmark forecasts, you can convert them into two-party vote shares. This yields figures of 53.6% for Clinton and 46.4% for Trump.

Results vs. other polls

If we look at an average of New Hampshire polls, Clinton's two-party vote share is currently at 54.5%. This value is 0.9 percentage points higher than her corresponding numbers in the UMass Lowell/7News poll. This margin is within the poll's error margin, which means that the poll is not an outlier.

Comparison to the combined PollyVote

The current PollyVote predicts Clinton to gain 54.2% of the two-party vote in New Hampshire. That is, Polly's prediction is 0.6 points above her polling numbers. The PollyVote forecast is thus in line with the poll's margin of 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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