Results of a new poll conducted by Gravis were announced. The poll asked respondents from Nevada for whom they will vote: Republican Donald Trump or Democrat Hillary Clinton.
Historically, Nevada has been a swing state, in which neither the Republican Party nor the Democratic Party has had overwhelming support to secure its electoral college votes. Hence, predictions in this state are of particular importance.
Gravis poll results
According to the results, billionaire Donald Trump and former First Lady Hillary Clinton have the same level of support, each with 46.0% of the vote.
The poll was in the field between October 25 and October 25. The sample size was 875 registered voters. If one takes into account the poll's error margin of +/-3.3 percentage points, the results reflect a statistical tie.
Putting the results in context
As any other method, polls are subject to bias. Hence, don't put too much trust in the results of a single poll. Rather than trusting the results from single polls, the best practice scientific advice is to use combined polls or, even better, a combined forecast that uses forecasts from different methods, each of which draws upon different data.
For the following comparison, we translate the candidates' raw poll numbers into two-party vote shares. The results of the actual poll mean 50.0 % for Clinton and 50.0 % for Trump in the two-party vote share.
Results in comparison to other polls
If we look at an average of Nevada polls, Clinton's current two-party vote share is at 50.9%. In comparison to the average forecast of other polls Clinton performed 0.9 percentage points worse in the poll. This deviation is outside the poll's margin of error, which suggests that the poll is an outlier.
Results compared to the combined PollyVote forecast
The most recent PollyVote predicts Clinton to gain 52.5% and Trump 47.5% of the two-party vote in Nevada. Clinton has 2.5 percentage points less when the results of the poll are compared to the combined PollyVote forecast for Nevada. Again, a look at the poll's sampling error indicates that this difference is significant.