Thursday, November 10, 2016

The Data Said Clinton Would Win. Why You Shouldn’t Have Believed It. - The New York Times

Also difficult to factor in recently influential variables such as the mainstream media giving an outlier candidate ~infinite free coverage in order to boost their advertising profits; recommended reading in this context: The Attention Merchants

"In addition to the polling errors, data scientists said the inherent weakness of election models might have caused some forecasting errors. Before an election, forecasters use a combination of historical polls and recent polling data to predict a candidate’s chance of winning. Some may also factor in other variables, such as giving higher weight to a candidate who is an incumbent.

But even with decades of polls to analyze, it is difficult for forecasters to predict accurately a candidate’s chance of winning the presidency months or even weeks ahead of time. Dr. Mutalik of Yale compared election modeling to weather forecasting."
The Data Said Clinton Would Win. Why You Shouldn’t Have Believed It. - The New York Times
Post a Comment