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Dead heat between Trump and Clinton in new LA Times poll

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

LA Times poll results
44

Clinton

46

Trump

Of those who answered the question, 44.0% said that they are going to vote for former New York Senator Hillary Clinton, whereas 46.0% revealed that they would give their vote to billionaire Donald Trump.

The poll was conducted between October 21 and October 27. The sample size was 3238 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. As a result, a good strategy is to not have too much faith in the results of an individual poll. Rather than relying on results from single polls, the recommended strategy consult combined polls or, even better, a combined forecast that draws upon different methods and data.

For the following comparison, we convert the candidates' raw poll numbers into shares of the two-party vote. The corresponding figures are 48.9% for Clinton and 51.1% for Trump. On October 26 Clinton received 50.0% in the LA Times poll and Trump received only 50.0%.

Results in comparison to other polls

Looking at an average of polls, Trump's current two-party vote share is at 46.8%. This value is 4.3 percentage points lower than corresponding numbers in the LA Times poll. This margin is within the poll's error margin, which suggests that the poll is not an outlier.

The poll in comparison with PollyVote's prediction

The latest PollyVote foresees Trump to gain 46.1% of the two-party vote. Hence, the combined PollyVote is 5.0 points below polling numbers. Again, a look at the poll's sampling error 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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