Key Takeaways Linear regression models the relationship between a dependent and independent variable (s). A linear regression essentially estimates a line of best fit among all variables in the model.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

As in Excel, we can manually remove explanatory variables one-by-one until we have a model in which all the explanatory variables are significant. This is the essence of data-driven (versus theory ...

We propose a multivariate sparse group lasso variable selection and estimation method for data with highdimensional predictors as well as high-dimensional response variables. The method is carried out ...