The outcome of the presidential election shocked almost everyone. Most polls and model-based forecasts (like FiveThirtyEight and Upshot) predicted a Clinton victory, only to be proven wrong by Trump wins in almost every swing state, plus a couple states no one thought would ever go his way.
So what happened? We gathered a bunch of smart data scientists and political insiders to get to the bottom of this.
- Natalie Jackson, Senior Polling Editor at the Huffington Post
- Andrew Therriault, former Director of Data Science at the Democratic National Committee
- Mark Stephenson, founder of Red Oak Strategic, the data team behind many Republican campaigns
- Joel Grus, author of Data Science from Scratch and co-host of the new podcast Adversarial Learning
- Renee Teate, host of the fabulously popular Becoming a Data Scientist podcast
- Andrew Musselman, Chief Data Scientist at Accenture and co-host of the new podcast Adversarial Learning
Huge thanks to our panel!
Author
Partially Derivative
Partially Derivative is a podcast about data science hosted by Chris Albon, Jonathon Morgan, and Vidya Spandana. @partiallyd