Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

We look at the problem of predicting several response variables from the same set of explanatory variables. The question is how to take advantage of correlations between the response variables to ...

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 ...

Acquire an understanding of the concepts surrounding 'collinearity'. Appreciate the indications and symptoms of collinearity in multivariable regression. Become aware of the available diagnostic tools ...

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 ...

In order to introduce the concepts underlying multiple linear regression, it is necessary to be familiar with and understand the basic theory of simple linear regression on which it is based.

Orthogonal regression is one of the standard linear regression methods to correct for the effects of measurement error in predictors. We argue that orthogonal ...