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Florida: New Quinnipiac poll shows Clinton trailing by 3 points


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

In Florida, the election outcome 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.

Quinnipiac poll results




The results show that 39.0% of respondents indicated that they would cast a ballot for former New York Senator Hillary Clinton, whereas 42.0% indicated that they would cast a ballot for real estate developer Donald Trump.

This poll was conducted from June 30 to July 11, among a random sample of 1015 registered voters. The error margin is +/-3.1 percentage points, which means that the levels of voter support for both parties' candidates do not differ significantly.

Putting the results in context

Single polls can contain large biases, and should be treated with caution. Instead of relying on results from single polls, one should look at combined polls or, even better, a combined forecast that relies on different methods and data.

In order to make the results comparable to benchmark forecasts, you can convert them into two-party vote shares. The corresponding figures are 48.2% for Clinton and 51.9% for Trump.

Results compared to other polls

Trump is currently at 50.2% of the two-party vote in an average of recent polls in Florida. This value is 1.7 percentage points lower than his respective numbers in the Quinnipiac poll. This margin is within the poll's margin of error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote anticipates Trump to gain 50.3% of the two-party vote in Florida. This means that the combined PollyVote is 1.6 points below his polling numbers. The PollyVote forecast is therefore within the poll's sampling 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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