For example, instead of having a factor “city” with many different levels/values {West Vancouver, North Vancouver, Chilliwack, Kelowna, Prince George, …}, it might be better to group cities by region ...

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

You perform a multiple linear regression analysis when you have more than one explanatory variable for consideration in your model. You can write the multiple linear regression equation for a model ...

For example, you might want to predict an employee's salary based on age, height, years of experience, and so on. There are approximately a dozen common regression techniques. The most basic technique ...

Regression is a statistical method that allows us to look at the relationship between two variables, while holding other factors equal.

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 ...

First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals ...

I explore the use of multiple regression on distance matrices (MRM), an extension of partial Mantel analysis, in spatial analysis of ecological data. MRM involves a multiple regression of a response ...

Further statistics in dentistry: 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 ...