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Minnesota: New KSTP/SurveyUSA poll shows Clinton with 6 points lead

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On October 10, KSTP/SurveyUSA released the results of a new poll, in which respondents from Minnesota were asked for whom they will vote: Democrat Hillary Clinton or Republican Donald Trump.

KSTP/SurveyUSA poll results
49

Clinton

43

Trump

Of those who answered the question, 49.0% said that they would vote for former New York Senator Hillary Clinton, whereas 43.0% declared that they would give their vote to real estate developer Donald Trump.

The poll was carried out between September 16 and September 20. The sample size was 625 likely voters. If one accounts for the poll's error margin of +/-4.0 percentage points, the results reflect a statistical tie.

Putting the results in context

As a general rule, however, don't have too much faith in the results of single polls, as they often contain large errors. Instead of relying on results from single polls, the best practice is to consult combined polls or, even better, a combined forecast that uses 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. The corresponding figures are 53.3% for Clinton and 46.7% for Trump. For comparison: Only 48.3% was obtained by Clinton in the KSTP/SurveyUSA poll on November 2, for Trump this number was 51.7%.

Comparison to other polls

Clinton currently achieves 52.7% of the major two-party vote in an average of recent polls in Minnesota. Compared to her numbers in the KSTP/SurveyUSA poll Clinton's poll average is 0.7 percentage points lower. 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 most recent PollyVote forecasts Clinton to gain 55.3% of the two-party vote in Minnesota. Hence, the combined PollyVote is 2.0 points above her polling numbers. Again, a look at the poll's sampling error reveals that this difference 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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