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 ...

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.

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 ...

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

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 ...

Regression is a statistical method that allows us to look at the relationship between two variables, while holding other factors equal. This post will show how to estimate and interpret linear ...

This article introduces the multivariate regression-discontinuity design (MRDD), where multiple assignment variables and cutoffs may be used for treatment assignment. For an MRDD with two assignment ...