In regression analysis, a dummy variable is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. For example, in econometric time series analysis, dummy variables may be used to indicate the occurrence of wars, or major strikes. In statistics, regression analysis is used to model relationships between random variables, determine the magnitude of the relationships between variables, and can be used to make predictions based on the models. ... Econometrics literally means economic measurement. It is a combination of mathematical economics, statistics, economic statistics and economic theory. ... In statistics and signal processing, a time series is a sequence of data points, measured typically at successive times, spaced apart at uniform time intervals. ...

Dummy variables may be extended to more complex cases. For example, seasonal effects may be captured by creating dummy variables for each of the seasons.

However, if a constant term is included in the regression, it is important to exclude one of the dummy variables from the regression, making this the base category against which the others are assessed. If all the dummy variables are included, their sum is equal to the constant term, resulting in perfect multicollinearity. This is referred to as the dummy variable trap. In mathematics and the mathematical sciences, a constant is a fixed, but possibly unspecified, value. ... Multicollinearity refers to linear inter-correlation among variables. ...

• See also Free variables and bound variables