Your question is Linear Regression Assumptions. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the assumptions behind basic linear regression and what happens when they are violated.
Discuss the assumptions required for ordinary least squares estimation and inference, including linearity, independent errors, exogeneity, constant error variance, and normally distributed errors where relevant. For each assumption, state its consequence when violated and identify an appropriate diagnostic or remedy. Distinguish effects on coefficient bias, consistency, standard errors, confidence intervals, and hypothesis tests.