The Assumptions of Ordinary Least Squares - a podcast by Ben Jaffe and Katie Malone

Ordinary least squares (OLS) is often used synonymously with linear regression. If you’re a data scientist, machine learner, or statistician, you bump into it daily. If you haven’t had the opportunity to build up your understanding from the foundations, though, listen up: there are a number of assumptions underlying OLS that you should know and love. They’re interesting, force you to think about data and statistics, and help you know when you’re out of “good” OLS territory and into places where you could run into trouble.

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone