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KOB-TV/SurveyUSA*KOB-TV/SUSA* poll in New Mexico: Trump trails by 13 points

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Results of a new poll conducted by KOB-TV/SurveyUSAKOB-TV/SUSA were circulated. The poll asked respondents from New Mexico for whom they will vote: Donald·Trump or Hillary·Clinton.

KOB-TV/SurveyUSAKOB-TV/SUSA poll results
46

Clinton

33

Trump

According to the results, 46.0% of interviewees indicated that they would give their vote to former First Lady Hillary Clinton, whereas 33.0% intend to vote for billionaire Donald Trump.

The poll was conducted from September 28 to October 2. A total of 594 likely voters responded. The sampling error is +/-4.1 points. This means that the poll results 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 have too much faith in the results of a single poll. Instead of relying on results from single polls, forecasting research recommends to look at combined polls or, even better, the combined PollyVote forecast that draws upon forecasts from different methods, each of which draws upon different data.

For the following analysis, we convert Clinton's and Trump's raw poll numbers into two-party vote shares. The respective figures are 58.2% for Clinton and 41.8% for Trump.

Results in comparison to other polls

Clinton currently achieves 57.3% of the two-party vote in an average of recent polls in New Mexico. Compared to her numbers in the KOB-TV/SurveyUSAKOB-TV/SUSA poll Clinton's poll average is 0.9 percentage points lower. This difference is within the poll's sampling error, which suggests that the poll is not an outlier.

Comparison to the combined PollyVote

The current PollyVote expects Clinton to gain 55.3% of the two-party vote in New Mexico. This means that Polly's forecast is 2.9 points below her polling numbers. The PollyVote forecast is therefore within the poll's margin of 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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