1. Introduction -- A review of multiple regression -- 2. Creating dummy variables -- Choosing a reference group -- Descriptive statistics -- Distributional statistics -- Correlation -- Partial correlations -- 3. Using dummy variables as regressors -- Regression with one dummy variable -- Regression with multiple dummy variables -- Assessing differences between specified categories -- Adding a second qualitative measure -- Predicted values -- Adding quantitative variables to the specification -- 4. Assessing group differences in effects -- Specifying interaction effects -- Separate subgroup regressions -- Dealing with heteroscedasticity -- Interpreting dummy variables in semilogarithmic equations -- Testing for heteroscedasticity with more than two groups -- Methods for making multiple comparisons with nonindependent tests -- 5. Alternative coding schemes for dummy variables -- Effects-coded dummy variables -- Regression results -- Contrast-coded dummy variables -- Regression results -- 6. Special topics in the use of dummy variables -- Dummy variables in logit models -- Testing for curvilinearity -- Piecewise linear regression -- Dummy variables in time-series data -- Dummy variables and autocorrelation -- 7. Conclusions.