In Antevorta we looked at how we could incorporate categorical predictors into the linear model. Before that we spent some considerable time looking at continuous predictors. What happens when you have both? Not a lot really, you can add and subtract predictors from the model as you see fit (with relation to your specific research hypotheses).
When the goal is to look at differences between group means while accounting for one or more other predictors that are continuous, people tend to refer to it as analysis of covariance or ANCOVA. However, as is becoming a familiar theme, this situation is just a particular case of the linear model that combines categorical and continuous predictors. This tutorial looks at this situation and gives you some practical experience.