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Arizona: Clinton holds slim advantage in new Predictive Insights poll


On August 1, Predictive Insights released the results of a new poll, in which respondents from Arizona were asked for whom they will vote: Republican nominee Donald Trump or Democrat nominee Hillary Clinton.

Predictive Insights poll results




According to the results, 47.0% of interviewees are going to give their vote to former Secretary of State Hillary Clinton, whereas 42.0% are going to give their vote to billionaire Donald Trump.

The poll was conducted from June 20 to June 20 with 1060 likely voters. There is a sampling error of +/-3.0 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

In general, however, one should not have too much faith in the results of single polls, as they can contain large errors. Instead of trusting the results from single polls, forecasting research recommends to use combined polls or, even better, the combined PollyVote forecast that uses forecasts from different methods, each of which uses different data.

To make the results comparable to forecasts from benchmark methods, one can convert them into two-party vote shares. This yields figures of 52.8% for Clinton and 47.2% for Trump.

Comparison to other polls

Clinton is currently at 50.3% of the major two-party vote according to an average of recent polls in Arizona. This value is 2.5 percentage points lower than her corresponding numbers in the Predictive Insights poll. 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 45.9% of the two-party vote in Arizona. That is, Polly's combined forecast is 6.9 points below her polling numbers. Again, a look at the poll's error margin shows that this difference 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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