Assumptions of Linear Regression

Linear regression is a modeling approach that attempts to establish a relationship between a dependent variable and one or more independent variables by fitting a linear equation. There are five assumptions of linear regression. This is what is going to be covered in this blog post.

Linear Relationship

Normal distribution

No or little multicollinearity

No auto-correlation

Homoscedasticity

References