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Clinton tied with Trump in latest LA Times poll

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LA Times published the results of a new national poll. In this poll, interviewees were asked for whom they will vote: Democrat Hillary Clinton or Republican Donald Trump.

LA Times poll results
45

Clinton

45

Trump

According to the results, the two candidates can draw on identical levels of support, each with 45.0% of the vote.

The poll was carried out between October 20 and October 26. The sample size was 3208 participants. There is a sampling error of +/-4.5 percentage points. Considering this error margin, the race is currently a statistical tie.

Putting the results in context

As any other method, polls are subject to bias. Thus, as a general rule, don't be overly confident the results of an individual poll. Instead of relying on results from single polls, the recommended strategy use combined polls or, even better, a combined forecast that draws upon forecasts from different methods, each of which draws upon different data.

In order to make the results comparable to benchmark forecasts, we translate them into two-party vote shares. The results of the actual poll mean 50.0 % for Clinton and 50.0 % for Trump concerning the two-party vote share. On October 25 Clinton received only 49.4% in the LA Times poll and Trump received 50.6%.

Comparison to other polls

An average of recent polls has Clinton at 53.4% of the two-party vote. When compared to the average forecast of other polls Clinton performed 3.4 percentage points worse in the poll. This margin is outside the poll's error margin, which means that the poll is an outlier.

Comparison to the combined PollyVote

The most recent PollyVote predicts Clinton to gain 54.0% and Trump 46.0% of the two-party vote. Clinton has 4 percentage points less when the results of the poll are compared to the combined PollyVote forecast. 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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