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Colorado: Dead heat between Clinton and Trump in latest Gravis poll

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Results of a new poll conducted by Gravis were circulated. The poll asked interviewees from Colorado for whom they would vote if the Democratic Party nominated Hillary Clinton and the Republican Party nominated Donald Trump.

Historically, Colorado has been a battleground state, in which neither the Democrats nor the Republicans have had overwhelming support to clinch its electoral college votes. This is why forecasts here are of particular importance.

Gravis poll results
43

Clinton

41

Trump

According to the results, 43.0% of interviewees will give their vote to former New York Senator Hillary Clinton, whereas 41.0% plan to vote for real estate developer Donald Trump.

The poll was carried out from July 7 to July 8 among 1313 adults. There is a sampling error of +/-2.7 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

Individual polls should be treated with caution, as they may contain substantial biases. Instead of trusting the results from single polls, one should use combined polls or, even better, a combined forecast that draws upon different methods and data.

For the following analysis, we translate Clinton's and Trump's raw poll numbers into two-party vote shares. This yields figures of 51.2% for Clinton and 48.8% for Trump.

Comparison to other polls

An average of recent polls in Colorado has Clinton at 54.9% of the two-party vote. This value is 3.7 percentage points higher than her respective numbers in the Gravis poll. This deviation is outside the poll's error margin, which means that the poll is an outlier.

The poll compared with PollyVote's forecast

The most recent PollyVote foresees Clinton to gain 52.8% of the two-party vote in Colorado. Hence, the combined PollyVote is 1.6 points above her polling numbers. The PollyVote forecast is thus within 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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