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Quinnipiac poll in Connecticut: Clinton holds healthy lead

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On July 15, Quinnipiac released the results of a new poll, in which respondents from Connecticut were asked for whom they would vote if the nominees were Hillary Clinton for the Democrats and Donald Trump for the Republicans.

Quinnipiac poll results
45

Clinton

38

Trump

According to the results, 45.0% of respondents plan to vote for former Secretary of State Hillary Clinton, while 38.0% would vote for businessman Donald Trump.

The poll was carried out from June 1 to June 5 among 1330 registered voters. There is a sampling error of +/-2.7 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

In general, however, you should not have too much faith in the results of single polls, because they sometimes contain large errors. Instead of trusting the results from single polls, the best practice is to consult combined polls or, even better, the combined PollyVote forecast that uses different methods and data.

For the following analysis, we convert the candidates' raw poll numbers into two-party vote shares. This yields figures of 54.2% for Clinton and 45.8% for Trump. On April 26 Clinton obtained only 54.0% in the Quinnipiac poll and Trump obtained 46.0%.

Results in comparison to other polls

Clinton currently achieves 53.7% of the two-party vote in an average of recent polls in Connecticut. In comparison to her numbers in the Quinnipiac poll Clinton's poll average is 0.5 percentage points lower. This deviation is within the poll's sampling error, which means that the poll is not an outlier.

The poll compared with PollyVote's forecast

The current PollyVote forecasts Clinton to gain 54.5% of the two-party vote in Connecticut. Hence, Polly's combined forecast is 0.3 points above her polling numbers. Again, a look at the poll's error margin shows 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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