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Detroit Free Press poll in Michigan: Clinton with 10 points lead

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Results of a new poll conducted by Detroit Free Press were spread. The poll asked respondents from Michigan for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

Detroit Free Press poll results
46

Clinton

36

Trump

Of those who responded, 46.0% said that they intend to vote for former New York Senator Hillary Clinton, whereas 36.0% declared that they would give their vote to billionaire Donald Trump.

The poll was in the field between October 1 and October 3. The sample size was 600 likely voters. There is a sampling error of +/-4.0 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

Single polls often include large errors, which is why they should be interpreted with caution. Instead of relying on results from single polls, the evidence-based approach is to rely on combined polls or, even better, the combined PollyVote forecast that relies on forecasts from different methods, each of which draws upon different data.

For the following comparison, we translate the candidates' raw poll numbers into two-party vote shares. This procedure yields figures of 56.1% for Clinton and 43.9% for Trump.

Results in comparison to other polls

Clinton is currently at 57.0% of the major two-party vote according to an average of recent polls in Michigan. In comparison to her numbers in the Detroit Free Press poll Clinton's poll average is 0.9 percentage points higher. This margin is within the poll's margin of error, which suggests that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The current PollyVote foresees Clinton to gain 54.8% of the two-party vote in Michigan. That is, the PollyVote is 1.3 points below her polling numbers. The PollyVote forecast is thus 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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