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Comfortable lead for Clinton in recent Bloomberg/Selzer poll


Bloomberg/Selzer released the results of a new national poll, in which respondents were asked for whom they will vote: Hillary Clinton or Donald Trump.

Bloomberg/Selzer poll results




According to the results, 50.0% of participants indicated to vote for former First Lady Hillary Clinton, whereas 41.0% would vote for real estate developer Donald Trump.

The phone poll was conducted from October 14 to October 17 with 1006 likely voters. There is a sampling error of +/-3.2 percentage points. Considering this error margin, the gap between both candidates is statistically significant.

Putting the results in context

As a general rule, however, you should not have too much faith in the results of single polls, as they often contain large errors. Rather than trusting the results from single polls, forecasting research recommends to look at combined polls or, even better, the combined PollyVote forecast that incorporates forecasts from different methods, each of which draws upon different data.

In order to make the results comparable to benchmark forecasts, you can convert them into shares of the two-party vote. This yields figures of 55.0% for Clinton and 45.1% for Trump. On September 24 Clinton received only 50.0% in the Bloomberg/Selzer poll and Trump received 50.0%.

Results in comparison to other polls

An average of recent polls has Clinton at 53.7% of the two-party vote. This value is 1.4 percentage points lower than respective numbers in the Bloomberg/Selzer poll. This deviation is within the poll's error margin, which means that the poll is not an outlier.

Results compared to the combined PollyVote prediction

The current PollyVote forecasts Clinton to gain 53.9% of the two-party vote. Hence, Polly's forecast is 1.1 points below polling numbers. Again, a look at the poll's sampling error indicates 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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