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MRG poll in Michigan: Trump behind by 8 points

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

MRG poll results
46

Clinton

38

Trump

Of those who responded, 46.0% said that they will vote for former New York Senator Hillary Clinton, while 38.0% declared that they would give their vote to businessman Donald Trump.

The poll was conducted from October 16 to October 19. A total of 600 likely voters responded. The sampling error is +/-4.0 points. This means that the poll results for the two candidates differ significantly.

Putting the results in context

As any other method, polls are subject to bias. As a result, a good strategy is to not have too much faith in the results of an individual poll. Rather than relying on results from single polls, we recommend 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.

In order to make the results comparable to benchmark forecasts, you can convert them into two-party vote shares. The corresponding figures are 54.8% for Clinton and 45.2% for Trump. For comparison: Only 53.0% was obtained by Clinton in the MRG poll on February 27, for Trump this number was 47.0%.

Results in comparison to other polls

Looking at an average of Michigan polls, Clinton's current two-party vote share is at 56.5%. This value is 1.7 percentage points higher than her corresponding numbers in the MRG poll. This difference is within the poll's margin of error, which means that the poll is not an outlier.

The poll compared with PollyVote's forecast

The latest PollyVote foresees Clinton to gain 54.9% of the two-party vote in Michigan. This means that Polly's forecast is 0.1 points above her polling numbers. The PollyVote forecast is thus within the poll's error margin.

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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