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Latest Rasmussen Reports*Rasmussen* poll in Nevada: Trump and Clinton in a virtual tie

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Results of a new poll carried out by Rasmussen ReportsRasmussen were announced. The poll asked participants from Nevada for whom they will vote: Republican Donald Trump or Democrat Hillary Clinton.

Historically, Nevada has been a battleground state, in which no single party has had overwhelming support to secure that state's electoral college votes. Hence, forecasts in this state are of particular value.

Rasmussen ReportsRasmussen poll results
39

Clinton

42

Trump

Of those who responded, 39.0% said that they would vote for former First Lady Hillary Clinton, whereas 42.0% indicated that they would give their vote to real estate developer Donald Trump.

The poll was carried out from September 16 to September 18 with 800 likely voters. There is a sampling error of +/-4.0 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. In general, you should not have too much faith in the results of a single poll. At least, one should check how a poll's results compare to benchmark forecasts.

For the following analysis, we translate the candidates' raw poll numbers into shares of the two-party vote. The corresponding figures are 48.2% for Clinton and 51.9% for Trump.

Results in comparison to other polls

An average of recent polls in Nevada has Trump at 50.3% of the two-party vote. This value is 1.6 percentage points lower than her corresponding numbers in the Rasmussen ReportsRasmussen poll. This difference is within the poll's sampling error, which means that the poll is not an outlier.

Comparison to the combined PollyVote

The most recent PollyVote predicts Trump to gain 49.1% of the two-party vote in Nevada. That is, the combined PollyVote is 2.8 points below her polling numbers. The PollyVote forecast is therefore 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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