When parameters of a general linear model are estimated, analysts often report the main effects. However, sometimes the hypothesis of interest is a linear combination of the main effects that is not displayed by default in a standard regression table. Testing many hypotheses from the same linear model is especially relevant when an analyst fits a model using categorical variables where many post-hoc hypotheses are of interest. This presentation will show how to code a categorical variable for use in the general linear model and use tests of the so-called general linear hypothesis to test any number of hypotheses about the effects.