Multiple linear regression uses two or more independent variables to predict a dependent variable. The result is an equation you can use to estimate future outcomes based on known data.

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 ...

Reviewed by Thomas J. Catalano Fact checked by Melody Kazel Linear Regression vs. Multiple Regression: An Overview Linear regression (also called simple regression) is one of the most common ...

For example, you might want to predict an employee's salary based on age, height, high school grade point average, and so on. There are approximately a dozen common regression techniques. The most ...

- Multiple linear regression formula. The equation for multiple linear regression extended to two explanatory variables (x 1 and x 2) is as follows: This can be extended to more than two explanatory ...

Prediction is often the primary goal of data analysis. In this work, we propose a novel model averaging approach to the prediction of a functional response variable. We develop a crossvalidation model ...