In the seventh lesson of the series we’ll discuss some methods for comparing linear regression models. In the process, we’ll learn about the problem of overfitting and investigate some of the pros and cons of various evaluation methods (such as R-squared, adjusted R-squared, log likelihood, AIC, and BIC). We’ll also continue to practice our Python…