If a linear regression model is used for prediction, the mean squared error of prediction (MSEP) measures the performance of the model. The MSEP is a function of unknown parameters and good estimates ...

8.2. Linear regression with a single explanatory variable There are many ways to do linear regression in Python. We have already used the heavyweight Statsmodels library, so we will continue to use it ...

Residual plots can be used to validate assumptions about the regression model.

The mean square error criterion suggests a framework for thinking about the problem of multicollinearity in a linear model. To this end we present some examples to illustrate the linkage of the mean ...

Simple Linear Regression: Finding Trends The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to see if there's a relationship ...