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Trump leads in Nevada by 4 points in new Remington Research (R) poll


Remington Research (R) published the results of a new poll. In this poll, respondents from Nevada were asked for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

In Nevada, the popular vote is often close. Therefore, the state is commonly considered a purple state, which makes it particularly interesting from a forecasting perspective.

Remington Research (R) poll results




The results show that 44.0% of interviewees will cast a ballot for former First Lady Hillary Clinton, whereas 48.0% plan to vote for real estate developer Donald Trump.

This poll was conducted from October 30 to October 30, among a random sample of 1176 likely voters. There is a sampling error of +/-2.9 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

In general, however, one should not have too much faith in the results of single polls, since they sometimes contain large errors. At the very least, one should check how a poll's results compare to benchmark forecasts.

For the following comparison, we translate Trump's and Clinton's raw poll numbers into two-party vote shares. The corresponding figures are 47.8% for Clinton and 52.2% for Trump.

Comparison to other polls

If we look at an average of Nevada polls, Trump's current two-party vote share is at 49.2%. This value is 3 percentage points lower than her corresponding numbers in the Remington Research (R) poll. This deviation is outside the poll's margin of error, which means that the poll is an outlier.

Comparison to the combined PollyVote

The latest PollyVote forecasts Trump to gain 47.6% of the two-party vote in Nevada. This means that Polly's combined forecast is 4.6 points below her polling numbers. Again, a look at the poll's error margin suggests that this difference is significant.

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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