Introduction

Introduction

Real data is noisy. If you collect 100 measurements to fit a line with 2 parameters, the 100 equations will almost never agree perfectly — the system has no exact solution. Instead of giving up, we find the $\mathbf{x}$ that comes as close as possible. This idea, least squares, is exactly linear regression.