With less than a month until Election Day, you may be paying more attention to political polls, and starting to wonder how much you ought to trust them.
Polls are a useful tool for developing a sense of what issues are top of mind for voters and where the race between Vice President Kamala Harris and former President Donald J. Trump stands. But polling isn’t an exact science; it’s susceptible to common errors and baked-in biases. This is particularly true of election polls.
“Polling is often as much, or more, of an art than a science,” said Ashley Koning, director of the Eagleton Center for Public Interest Polling at Rutgers.
In a previous article about understanding polls, I went over what to look for in an individual poll. Here, let’s dive into common errors that challenge pollsters, how they mitigate those errors and how to think about sources of error as you interpret pre-election polls.
Polls’ potential pitfallsTheoretically, the only way to create a perfect survey of what every American thinks is to poll every American (though even the U.S. census has flaws). Clearly, that is not feasible, so instead, pollsters who want to measure public opinion survey a sample of the U.S. population. “I like to equate it to tasting a pot of soup,” Dr. Koning said. “You know from that one taste of soup how the rest of the pot tastes because it’s getting you a representative flavor of that pot.”
The spoonful-of-soup analogy helps demonstrate how pollsters can design a survey of just 1,000 people with the aim of representing 337 million. But it also shows why sampling is never truly precise.
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