# Why don't we use Manhattan distance instead of euclidean distance in linear regression?

When I am explaining concept of linear regression to one of my peers, I got stuck in answer this question. Why don`t we use Manhattan distance instead of euclidean distance in linear regression? Can anyone give intuition behind this?

• Least squares is easier to minimize than least absolute deviation (LAD) because the latter is non-differetial. Nowadays, LAD aka median regression is also quite frequently used. – Michael M Dec 25 '18 at 15:04