The statistical science behind polling

With so much uncertainty on the eve of the U.S. presidential election, one place we look for clarity is in the numbers. Pollsters learned valuable lessons from the 2016 election results that they’ve applied in the current election cycle to try to yield more accurate predictions. Host Alok Patel interviews a pollster and a statistician, delving into a brief history of political polling in the U.S, what went wrong in 2016, and how statistical concepts like data weighting and margin of error make all the difference in the accuracy of the poll.