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Clinton tied with Trump in new CBS poll


On July 14, CBS released the results of a new national poll sponsored by CBS News, in which respondents were asked for whom they would vote if the nominees were Hillary Clinton for the Democrats and Donald Trump for the GOP.

CBS poll results




According to the results, former New York Senator Hillary Clinton and real estate developer Donald Trump can draw on the same level of support, each with 40.0% of the vote.

This poll was conducted via phone from July 8 to July 12, among a random sample of 1358 participants. If one accounts for the poll's sampling error of +/-3.0 percentage points, the results reflect a statistical tie.

Putting the results in context

As a general rule, however, a good strategy is to not have too much faith in the results of single polls, because they can incorporate large errors. Rather, one should examine how a poll's results compare to benchmark forecasts.

To make the results comparable to forecasts from benchmark methods, you can translate them into shares of the two-party vote. The results of the actual poll mean 50.0 % for Clinton and 50.0 % for Trump concerning the two-party vote share. On June 15 Clinton obtained 53.8% in the CBS poll and Trump obtained only 46.3%.

Results vs. Other polls

When compared to the average results of other polls Clinton performed worse with 2.2 percentage points, while Trump did better with 2.2 percentage points. This deviation is outside the poll's sampling error, which suggests that the poll is an outlier.

Results compared to the combined PollyVote prediction

The most recent PollyVote predicts Clinton to gain 52.6% and Trump 47.4% of the two-party vote. Clinton has 2.6 percentage points less and Trump has 2.6 percentage points more when the results of the poll are compared to the combined PollyVote forecast. Again, a look at the poll's error margin suggests 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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