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Richard Stockton CollegeRichard Stockton College poll in New Jersey: Clinton holds marginal advantage

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Richard Stockton CollegeRichard Stockton College published the results of a new poll on October 10. In this poll, interviewees from New Jersey were asked for whom they will vote: Democrat candidate Hillary Clinton or Republican candidate Donald Trump.

Richard Stockton CollegeRichard Stockton College poll results
46

Clinton

40

Trump

Of those who answered the question, 46.0% said that they would vote for former Secretary of State Hillary Clinton, while 40.0% indicated that they would give their vote to real estate developer Donald Trump.

This poll was conducted from September 22 to September 29, among a random sample of 638 likely voters. There is a sampling error of +/-3.9 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

Individual polls should be regarded with caution, as they often incorporate large biases. At the very least, one should examine how a poll's results compare to benchmark forecasts.

For the following comparison, we convert Clinton's and Trump's raw poll numbers into shares of the two-party vote. The corresponding figures are 53.5% for Clinton and 46.5% for Trump.

Comparison to other polls

An average of recent polls in New Jersey sees Clinton at 56.3% of the two-party vote. In comparison to her numbers in the Richard Stockton CollegeRichard Stockton College poll Clinton's poll average is 2.8 percentage points better. 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 most recent PollyVote expects Clinton to gain 57.5% of the two-party vote in New Jersey. This means that Polly's forecast is 4.0 points above her polling numbers. Again, a look at the poll's error margin indicates that this deviation is significant.

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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