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New LA Times poll shows Trump with 4 points lead

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Results of a new national poll administered by LA Times were announced. The poll asked participants for whom they will vote: Republican Donald Trump or Democrat Hillary Clinton.

LA Times poll results
42

Clinton

46

Trump

Of those who replied, 42.0% said that they are going to vote for former Secretary of State Hillary Clinton, whereas 46.0% declared that they would give their vote to businessman Donald Trump.

This poll was conducted from September 18 to September 24, among a random sample of 2559 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. Hence, you should not be too confident the results of a single poll. Instead of trusting the results from single polls, the recommended strategy look at combined polls or, even better, the combined PollyVote forecast that uses forecasts from different methods, each of which draws upon different data.

To make the results comparable to forecasts from other methods, we convert them into two-party vote shares. This procedure results in values of 47.7% for Clinton and 52.3% for Trump. In the latest LA Times poll on September 2 Clinton obtained 51.7%, while Trump obtained only 0.0%.

Results in comparison to other polls

If we look at an average of polls, Trump's current two-party vote share is at 48.6%. Compared to numbers in the LA Times poll Trump's poll average is 3.7 percentage points worse. This difference is within the poll's margin of error, which means that the poll is not an outlier.

Results compared to the combined PollyVote forecast

The most recent PollyVote foresees Trump to gain 47.7% of the two-party vote. That is, Polly's prediction is 4.6 points below polling numbers. The PollyVote forecast is therefore outside the poll's sampling error.

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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