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WBUR/MassINC poll in Massachusetts: Trump trails by a whopping margin

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

WBUR/MassINC poll results
60

Clinton

31

Trump

According to the results, 60.0% of participants are going to vote for former First Lady Hillary Clinton, while 31.0% plan to vote for real estate developer Donald Trump.

This poll was conducted from September 7 to September 10, among a random sample of 506 likely voters. Given the poll's margin of error of +/-4.4 percentage points, the gap in voter support is statistically significant.

Putting the results in context

As a general rule, however, don't have too much faith in the results of single polls, since they often incorporate large errors. Instead of trusting the results from single polls, forecasting research recommends to consult combined polls or, even better, the combined PollyVote forecast that draws upon forecasts from different methods, each of which draws upon different data.

For the following analysis, we convert Trump's and Clinton's raw poll numbers into two-party vote shares. This procedure results in figures of 65.9% for Clinton and 34.1% for Trump.

Results in comparison to other polls

Looking at an average of Massachusetts polls, Clinton's two-party vote share is currently at 63.2%. Compared to her numbers in the WBUR/MassINC poll Clinton's poll average is 2.7 percentage points worse. This margin is within the poll's error margin, which means that the poll is not an outlier.

Comparison to the combined PollyVote

The current PollyVote predicts Clinton to gain 63.9% of the two-party vote in Massachusetts. This means that Polly's combined forecast is 2.0 points below her polling numbers. Again, a look at the poll's sampling error reveals that this deviation 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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