In
statistical modeling,
regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a
dependent variable and one or more
independent variables (or 'predictors'). More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the
conditional expectation of the dependent variable given the independent variables – that is, the
average value of the dependent variable when the independent variables are fixed. Less commonly, the focus is on a
quantile, or other
location parameter of the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a
function of the independent variables called the
regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function which can be described by a
probability distribution.