regression analysis is used to model the relationship between random variables: One or more response variables or dependent variables (usually named Y), and the predictors (also called input variables, independent variables or explanatory variables), usually named X1,...,Xp). If there is more than one response variable, we speak of multivariate regression, which is not covered in this article.

Regression analysis is most commonly associated with fitting a curve (function) to some set of measurement data (curve fitting), but it can have several objectives:

* Prediction of future observations, as by curve fitting
* Determining how closely the response can be predicted by the predictor
* Assessing the relationship between the predictors