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Monmouth poll in Florida: Trump trails by a clear margin


Monmouth released the results of a new poll, in which respondents from Florida were asked for whom they will vote: Donald Trump or Hillary Clinton.

Historically, Florida has been a swing state, in which neither of the two major parties has had overwhelming support to clinch that state's electoral college votes. This is why forecasts in this state are of particular interest.

Monmouth poll results




According to the results, 48.0% of interviewees will vote for former Secretary of State Hillary Clinton, while 39.0% are going to vote for real estate developer Donald Trump.

The poll was carried out from August 12 to August 15 among 402 likely voters. There is a sampling error of +/-4.9 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

Single polls should be treated with caution, since they often include large errors. Instead of trusting the results from single polls, the evidence-based approach is to rely on combined polls or, even better, a combined forecast that relies on different methods and data.

For the following analysis, we convert Trump's and Clinton's raw poll numbers into shares of the two-party vote. The respective figures are 55.2% for Clinton and 44.8% for Trump.

Results compared to other polls

Clinton currently runs at 51.2% of the major two-party vote in an average of recent polls in Florida. This value is 4 percentage points lower than her corresponding numbers in the Monmouth poll. This margin is within the poll's error margin, which means that the poll is not an outlier.

The poll compared with PollyVote's prediction

The current PollyVote foresees Clinton to gain 51.5% of the two-party vote in Florida. That is, the PollyVote forecast is 3.7 points below her polling numbers. The PollyVote forecast is thus within the poll's error margin.

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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