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Virginia: 7 points lead for Clinton in latest Christopher Newport Univ. Poll


Results of a new poll administered by Christopher Newport Univ. were released. The poll asked respondents from Virginia for whom they will vote: Hillary Clinton or Donald Trump.

In Virginia, the election outcome is usually close. This is the reason why the state is commonly referred to as a battleground state, which makes it particularly interesting from a forecasting perspective.

Christopher Newport Univ. Poll results




The results show that 46.0% of respondents indicated that they would cast a ballot for former New York Senator Hillary Clinton, while 39.0% indicated that they would cast a ballot for businessman Donald Trump.

The poll was conducted from October 23 to October 26 among 814 likely voters. There is a sampling error of +/-4.2 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. In general, a good strategy is to not rely too much on the results of an individual poll. At least, one should examine how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from other methods, you can translate them into two-party vote shares. This yields figures of 54.1% for Clinton and 45.9% for Trump.

Results in comparison to other polls

An average of recent polls in Virginia has Clinton at 54.6% of the two-party vote. Relative to her numbers in the Christopher Newport Univ. Poll Clinton's poll average is 0.5 percentage points higher. This difference is within the poll's error margin, which means that the poll is not an outlier.

Results compared to the combined PollyVote forecast

The latest PollyVote foresees Clinton to gain 54.4% of the two-party vote in Virginia. Hence, the PollyVote is 0.3 points above her polling numbers. The PollyVote forecast is thus within the poll's sampling 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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