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 extension of Lesson 9. I will start with a ...

Notes: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. [2] The condition number is large, 4.36e+05. This might indicate that there are strong ...

Linear regression, also called simple regression, is one of the most common techniques of regression analysis. Multiple regression is a broader class of regression analysis, which encompasses both ...