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<\/a>From the Pew Research Center assessment of the representatives of public opinion polls.<\/p><\/div><\/p>\n First, there’s the question of the act of polling itself. Like anytime you gather data for statistical analyses, there’s always a chance for sampling bias<\/a>. Since it’s impossible to contact every single person in the country, pollsters need to find some representative subset. That is, polls need to use a small number of opinions to extrapolate the national opinion<\/a>. National polls are typically conducted by phone, and Pew Research reports<\/a> that — largely due to the disappearance of land lines over the past 20 years — response rates have gone from 36% in 1997 to 9% in 2012. Since landlines can be autodialed while cell phones must be dialed by hand<\/a>, calling land lines is still the best way to reach the largest swath of people as fast as possible. <\/p>\n This of course brings with it some problem of bias, since the set of all land line owners in the United States is a very particular demographic, not necessarily representative of the country as a whole. But the Pew Research Center says that through careful weighting of poll responses<\/a> they are able to overcome these biases. So a single poll, which already contains thousands of responses is weighted to correct biases and massaged to give the most accurate picture of national opinion. <\/p>\n But typically the poll results that you see on popular news sites don’t just reflect a single poll, they are often aggregates of the top 5 state and national polls<\/a> in some cases, to several thousands of polls<\/a> in other cases. And then the thousands of polls — some of which are more reliable than others<\/a> — are weighted to reflect their reliability, sample size, and representative regional demographics. <\/p>\n And finally an aggregation of polls becomes and mathematical model when a few more factors are added into the mix. Depending on the agency doing the modeling they will factor in effects like the convention bounce<\/a>, the shape of the economy, and accuracy in prediction in certain states in past elections. All of these factors come together to build a robust<\/a> mathematical model to forecast the election. <\/p>\n As one example, The New York Times maintains an active “Who Will Be President?” Scoreboard<\/a>, comparing their aggregate model will several of the other top forecasts like fivethirtyeight<\/a>, Daily Kos<\/a>, HuffPost<\/a>, and Princeton Election Consortium<\/a>. And to game things out even further they also have an interactive chart weighing out the probabilities<\/a> of each candidates path to the presidency based on electoral votes and states that have determined election outcomes in the past. <\/p>\n And then there’s this dimly lit corner of election forecasting that doesn’t rely on polls at all. These are places like the Cook Political Report<\/a> which produces forecasts based more on reporting trends and expert opinions, or PredictWise<\/a> which bases its forecasting on a combination of polls and betting markets. <\/p>\n There are a host of quantitative ways to deal with the election right now — and some slightly more qualitative ways<\/a> as well<\/a> — but I find the best thing to do is light some aromatherapy candles, immerse yourself in a warm bath of polls and forecasting, breathe deep cleansing breaths, and wait for November 8th. <\/p>\n