An explanatory variable that assumes only two values, 0 or 1. In a regression analysis, the coefficient of a dummy variable shows the average effect on the level of the dependent variable when the dummy variable assumes the value of 1. For example, a dummy variable might represent the presence or absence of capital punishment in a geographical region, and its regression coefficient could show the effect of capital punishment on the level of violent crime. More than two categories can be handled by using additional dummy variables; for example, to represent three political affiliations (e.g., Republican, Democrat, or Other) in a model to predict election outcomes, one could use two dummy variables ("Republican or not?" and "Democrat or not?"). One needs *v*-1 dummy variables to represent *v* variables.