The present article discusses the role of categorical variable in the problem
of multicollinearity in linear regression model. It exposes the diagnostic tool
condition number to linear regression models with categorical explanatory variables
and analyzes how the dummy variables and choice of reference category
can affect the degree of multicollinearity. Such an effect is analyzed analytically
as well as numerically through simulation and real data application
