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Maryland: New Goucher College*Goucher College* poll shows Clinton with 33 points lead

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Goucher CollegeGoucher College published the results of a new poll. In this poll, participants from Maryland were asked for whom they will vote: Donald Trump or Hillary Clinton.

Goucher CollegeGoucher College poll results
58

Clinton

25

Trump

Of those who responded, 58.0% said that they would vote for former New York Senator Hillary Clinton, whereas 25.0% indicated that they would give their vote to real estate developer Donald Trump.

The poll was conducted from September 17 to September 20 with 514 likely voters. The sampling error is +/-4.3 percentage points, which means that the levels of voter support for both parties' candidates differ significantly.

Putting the results in context

In general, however, don't have too much faith in the results of single polls, since they may contain large errors. Rather than trusting the results from single polls, forecasting research recommends to use combined polls or, even better, a combined forecast that relies on forecasts from different methods, each of which relies on different data.

In order to make the results comparable to forecasts from other methods, we convert them into shares of the two-party vote. This procedure yields figures of 69.9% for Clinton and 30.1% for Trump.

Results in comparison to other polls

Looking at an average of Maryland polls, Clinton's current two-party vote share is at 69.2%. This value is 0.7 percentage points lower than her respective numbers in the Goucher CollegeGoucher College poll. This deviation is within the poll's error margin, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote anticipates Clinton to gain 64.4% of the two-party vote in Maryland. That is, Polly's prediction is 5.5 points below her polling numbers. The PollyVote forecast is thus outside the poll's margin of 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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