Statistics for Data Science and Business Analysis - A1. Linearity

The video tutorial explains linear regression, highlighting its simplicity and how to verify linearity using scatter plots. It discusses cases where linear regression is unsuitable due to nonlinear relationships and suggests transformations like exponential and logarithmic to address this. The video concludes with a brief mention of endogeneity of regressors, which will be covered in the next lesson.

What happens if you use a linear regression model on data that does not fit a straight line?

What is the next assumption to be discussed after linearity in regression analysis?