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Nevada: Clinton holds narrow lead in Monmouth poll


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

Nevada is traditionally a purple state, where Republicans and Democrats have often gained similar levels of voter support. Hence, the election outcome in that state is viewed as crucial in determining which party will win the majority of electoral votes.

Monmouth poll results




Of those who answered the question, 45.0% said that they intend to vote for former First Lady Hillary Clinton, whereas 41.0% said that they would give their vote to billionaire Donald Trump.

The poll was in the field between July 7 and July 10. The sample size was 408 likely voters. The margin of error is +/-4.9 percentage points, which means that the poll results for both candidates do not differ significantly.

Putting the results in context

As any other method, polls are subject to bias. As a result, a good strategy is to not be overly confident the results of a single poll. At least, one should check how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from benchmark methods, one can translate them into shares of the two-party vote. This procedure yields figures of 52.3% for Clinton and 47.7% for Trump.

Comparison to other polls

Clinton currently runs at 51.3% of the major two-party vote in an average of recent polls in Nevada. This value is 1 percentage point lower than her corresponding numbers in the Monmouth poll. This margin is within the poll's margin of error, which means that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The most recent PollyVote anticipates Clinton to gain 51.0% of the two-party vote in Nevada. Hence, the PollyVote forecast is 1.3 points below her polling numbers. Again, a look at the poll's margin of error indicates 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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