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FOX 2 Detroit/Mitchell poll in Michigan: Trump trails by a solid margin


Results of a new poll carried out by FOX 2 Detroit/Mitchell were circulated on October 12. The poll asked interviewees from Michigan for whom they will vote: Hillary Clinton or Donald Trump.

FOX 2 Detroit/Mitchell poll results




Of those who replied, 53.0% said that they will vote for former First Lady Hillary Clinton, whereas 41.0% revealed that they would give their vote to billionaire Donald Trump.

The poll was conducted from October 18 to October 18. A total of 1102 likely voters responded. The sampling error is +/-3.0 percentage points. This means that the levels of voter support for the candidates of both parties differ significantly.

Putting the results in context

Individual polls should be regarded with caution, since they often contain large errors. Rather than trusting the results from single polls, the evidence-based approach is to rely on combined polls or, even better, a combined forecast that incorporates different methods and data.

To make the results comparable to benchmark forecasts, we translate them into shares of the two-party vote. The respective figures are 56.4% for Clinton and 43.6% for Trump. In the latest FOX 2 Detroit/Mitchell poll on September 7 Clinton received only 52.8%, while Trump received 47.2%.

Comparison to other polls

Looking at an average of Michigan polls, Clinton's two-party vote share is currently at 56.5%. In comparison to her numbers in the FOX 2 Detroit/Mitchell poll Clinton's poll average is 0.1 percentage points higher. This margin 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 Clinton to gain 54.6% of the two-party vote in Michigan. That is, the PollyVote is 1.8 points below her polling numbers. The PollyVote forecast is therefore in line with 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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