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

Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

This example introduces the basic PROC REG graphics syntax used to produce a standard plot of data from the aerobic fitness data set (Example 55.1). A simple linear regression of Oxygen on RunTime is ...

For electronics, linear regression has many applications, including interpreting sensor data. You might also use it to generalize a batch of unknown components, for example.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Similar to Example 62.3, by incorporating auxilary information into a regression estimator, the procedure can produce more accurate estimates of the population characteristics that are of interest. In ...

Halbert White, Glenn M. MacDonald, Some Large-Sample Tests for Nonnormality in the Linear Regression Model, Journal of the American Statistical Association, Vol. 75, No. 369 (Mar., 1980), pp. 16-28 ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.