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Colorado: Trump and Clinton virtually tied in new CNN-ORC poll

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CNN-ORC published the results of a new poll. In this poll, interviewees from Colorado were asked for whom they will vote: Democrat candidate Hillary Clinton or Republican candidate Donald Trump.

Historically, Colorado has been a swing state, in which neither the Republican Party nor the Democratic Party has had overwhelming support to secure its electoral college votes. This is the reason why predictions in this state are of particular interest.

CNN-ORC poll results
49

Clinton

47

Trump

Of those who answered the question, 49.0% said that they will vote for former First Lady Hillary Clinton, while 47.0% declared that they would give their vote to billionaire Donald Trump.

The poll was carried out from September 20 to September 25 among 784 likely voters. There is a sampling error of +/-3.5 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

In general, however, you should not have too much faith in the results of single polls, as they may incorporate large errors. At least, one should examine how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from benchmark methods, we convert them into two-party vote shares. The resulting figures are 51.0% for Clinton and 49.0% for Trump.

Results vs. other polls

An average of recent polls in Colorado sees Clinton at 49.8% of the two-party vote. This value is 1.2 percentage points lower than her respective numbers in the CNN-ORC poll. This margin is within the poll's sampling error, which means that the poll is not an outlier.

Comparison to the combined PollyVote

The latest PollyVote foresees Clinton to gain 52.1% of the two-party vote in Colorado. This means that the PollyVote is 1.1 points above her polling numbers. The PollyVote forecast is therefore in line with 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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