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Florida: Trump and Clinton virtually tied in latest Suffolk University poll

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

In Florida, the popular vote is usually decided by a narrow margin. This is the reason why the state is commonly regarded as a purple state, which makes it particularly interesting from a forecasting perspective.

Suffolk University poll results
44

Clinton

45

Trump

Of those who replied, 44.0% said that they will vote for former First Lady Hillary Clinton, whereas 45.0% said that they would give their vote to billionaire Donald Trump.

The poll was conducted from September 19 to September 21 among 500 likely voters. If one accounts for the poll's margin of error of +/-4.4 percentage points, the results reflect a statistical tie.

Putting the results in context

In general, however, don't have too much faith in the results of single polls, as they can incorporate large errors. At the very least, one should examine how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from other methods, you can convert them into two-party vote shares. This procedure results in values of 49.4% for Clinton and 50.6% for Trump.

Results compared to other polls

An average of recent polls in Florida has Trump at 50.1% of the two-party vote. In comparison to her numbers in the Suffolk University poll Trump's poll average is 0.5 percentage points worse. This deviation is within the poll's sampling error, which suggests that the poll is not an outlier.

The poll compared with PollyVote's forecast

The most recent PollyVote foresees Trump to gain 48.9% of the two-party vote in Florida. This means that the PollyVote forecast is 1.7 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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