4 OLS from a assumptions to visualization

In this lecture, we will continue our discussion of linear OLS regression. We will first discuss the assumptions underlying OLS regression, such as linearity, homoscedasticity, independence, and normality. Then, we will learn how to deal with categorical predictors, such as using dummy variables. Finally, we will briefly discuss categorical outcomes. By the end of the lecture, you will be able to understand the assumptions of OLS regression, how to deal with categorical predictors, and how to visualize regression results.

Lecture 4 slides