In statistics, the dependent variable is the event studied and expected to change whenever the independent variable is altered. The dependent variables represent the output or outcome whose variation is being studied and the independent variables represent inputs or causes for variation. Models explain the effects that the independent variables have on the dependent variables. Independent variables may be included for other reasons, such as for their potential confounding effect. In simulation, the dependent variable is changed in response to changes in the independent variables.
In data mining, the depending variable is assigned a role as target variable while a dependent variable may be assigned a role as regular variable. In quasi-experiment, differentiating between dependent variable may be downplayed in favour of differentiating between those variables that can be altered by the researcher and those that cannot be altered by the researcher.
In mathematical modelling, there are dependent variables and independent variables. The dependent variables represent the output whose variation is being studied.