What are the assumptions required for linear regression?

Given the fact that data science involves business and IT, you can also guarantee that you will have multiple interview questions that specifically address the more technical components of the position.

A sample answer for this question could be:

“Linear regression has five key assumptions: linear relationship, multivariate normality, no or little multicollinearity, no auto-correlation, and homoscedasticity. With this, I would also check the model for normalization, slew adjustment, outlier detection, and other real-world issues.”