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Virginia: Strong advantage for Clinton in new Quinnipiac poll


Results of a new poll administered by Quinnipiac were distributed. The poll asked participants from Virginia for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

Historically, Virginia has been a battleground state, in which neither the Republican Party nor the Democratic Party has had overwhelming support to clinch that state's electoral college votes. Therefore, forecasts in this state are of particular importance.

Quinnipiac poll results




Of those who responded, 53.0% said that they intend to vote for former Secretary of State Hillary Clinton, while 40.0% declared that they would give their vote to businessman Donald Trump.

The poll was carried out between October 20 and October 26. The sample size was 749 likely voters. The error margin is +/-3.6 percentage points, which means that the poll results for the two candidates differ significantly.

Putting the results in context

Single polls may contain large biases, and should be treated with caution. Rather, one should examine how a poll's results compare to benchmark forecasts.

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 57.0% for Clinton and 43.0% for Trump.

Comparison to other polls

Looking at an average of Virginia polls, Clinton's two-party vote share is currently at 55.7%. In comparison to her numbers in the Quinnipiac poll Clinton's poll average is 1.3 percentage points worse. This margin is within the poll's margin of error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The most recent PollyVote predicts Clinton to gain 54.6% of the two-party vote in Virginia. Hence, the PollyVote forecast is 2.4 points below her polling numbers. Again, a look at the poll's error margin suggests 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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