Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

The bottom line is this: You cannot meaningfully compare the size of the regression coefficients to assess the most important effect—it is an apples-and-oranges comparison.

Lesson 10 Multiple Linear Regression The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Research on multiple comparison during the past 50 years or so has focused mainly on the comparison of several population means. Several years ago, Spurrier considered the multiple comparison of ...

The problem of assessing influence and detecting influential cases in multiple linear regression with incomplete data is considered. A case is said to be influential if appreciable changes in fitted ...