Polling is more art than science. Once again, American pollsters have shown that they aren't as good as we thought.
Understanding the confidence interval will help you grasp what an election poll is -- or is not -- saying. As you might have guessed, the media consistently gets it wrong.
Pollsters have taken a beating the last few years. Getting Brexit and the 2016 U.S. presidential election wrong were spectacular failures that shook the public's faith in prediction models. The media is largely to blame. People like Nate Silver are often portrayed as oracles and polls as divinely inspired. Anyone who questions their accuracy is attacked for rejecting science. But polls aren't science. Instead, they are some combination of fancy math (statistics) and art. If the underlying assumptions are wrong, or if the sampling methods are biased, then polls will be inaccurate.
Anyone remotely familiar with the scientific method understands that just like a ruler or a telescope, statistics is a tool. Scientists use the tool primarily for one purpose: To answer the question, "Is my data meaningful?" Properly used, statistics is one of science's most powerful tools. But used improperly, statistics can be highly misleading.
What is a scientific poll? First, it is a misnomer. There is nothing scientific about a poll. Second, it is conducted using sound statistical techniques. What's more, savvy politicos know that not just any poll will do.