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Florida: Virtual tie between Clinton and Trump in new Bloomberg poll

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

In Florida, the popular vote is often decided by a narrow margin. Therefore, the state is commonly viewed as a battleground state, which makes it particularly interesting from a forecasting perspective.

Bloomberg poll results
45

Clinton

46

Trump

Of those who replied, 45.0% said that they plan to vote for former First Lady Hillary Clinton, whereas 46.0% indicated that they would give their vote to billionaire Donald Trump.

This poll was conducted from October 21 to October 24, among a random sample of 953 likely voters. Taking into account the poll's error margin of +/-3.2 percentage points, the results reflect a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. In general, don't rely too much on the results of an individual poll. At the very least, one should examine how a poll's results compare to benchmark forecasts.

For the following analysis, we translate Clinton's and Trump's raw poll numbers into shares of the two-party vote. This procedure yields values of 49.5% for Clinton and 50.6% for Trump.

Results vs. other polls

Trump currently runs at 49.1% of the two-party vote in an average of recent polls in Florida. This value is 1.5 percentage points lower than her respective numbers in the Bloomberg poll. This difference is within the poll's sampling error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote forecasts Trump to gain 48.6% of the two-party vote in Florida. That is, the PollyVote forecast is 2.0 points below her polling numbers. Again, a look at the poll's margin of error suggests that this deviation is insignificant.

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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