The "goodness of fit" is definied as the sum of all the squares of the distances between the experimental points and the line, measured vertically. This parameter is often called "chi-squared" for ...

In this module, we will learn how to fit linear regression models with least squares. We will also study the properties of least squares, and describe some goodness of fit metrics for linear ...

Penalized least squares estimates provide a way to balance fitting the data closely and avoiding excessive roughness or rapid variation. A penalized least squares estimate is a surface that minimizes ...