Recently, I'm studying linear regression. I've heard that errors always follow normal distribution because they are supposed to do (in the point of they are noises). But suddenly I just wonders what if residuals of a linear regression follow other distribution rather than a normal distribution. I think I can interpret that there's a potential to approving the performance of the model because it implies that there are some data that I've didn't collect. It means irreducible errors can be reduced actually. But I'm not good at math, so I don't know it is right or not.
Once again, how can we interpret residuals of a linear regression doesn't follow other distribution and how can we utilize if they do?