I was going through the concept of Linear Regression and ran into the concept of deciding whether a Linear Regression Model is the best fit for your data by 5 assumptions:
- Multivariate normality
- Independence of errors
- Lack of multicollinearity
The following are a general introduction of the five assumptions, feel free to add more detail to these assumptions.