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Louisiana: New SMOR*SMOR* poll shows Clinton trailing by 16 points

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SMORSMOR released the results of a new poll, in which respondents from Louisiana were asked for whom they will vote: Democrat Hillary Clinton or Republican Donald Trump.

SMORSMOR poll results
33

Clinton

49

Trump

Of those who answered the question, 33.0% said that they will vote for former Secretary of State Hillary Clinton, whereas 49.0% revealed that they would give their vote to businessman Donald Trump.

The poll was carried out from September 15 to September 17 among 500 likely voters. The sampling error is +/-4.4 percentage points, which means that the levels of voter support for both candidates differ significantly.

Putting the results in context

As any other method, polls are subject to bias. Thus, as a general rule, one should not put too much trust in the results of a single poll. Rather than relying on results from single polls, we recommend to look at combined polls or, even better, the combined PollyVote forecast that incorporates different methods and data.

In order to make the results comparable to forecasts from other methods, you can convert them into two-party vote shares. This procedure results in figures of 40.2% for Clinton and 59.8% for Trump.

Results compared to other polls

Trump is currently at 59.5% of the two-party vote in an average of recent polls in Louisiana. In comparison to his numbers in the SMORSMOR poll Trump's poll average is 0.4 percentage points worse. This deviation is within the poll's error margin, which suggests that the poll is not an outlier.

The poll compared with PollyVote's prediction

The latest PollyVote foresees Trump to gain 57.4% of the two-party vote in Louisiana. Hence, Polly's combined forecast is 2.4 points below his polling numbers. Again, a look at the poll's margin of error indicates that this difference is negligible.

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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