# 8.10 - Summary

8.10 - SummaryIn this lesson, we briefly reviewed a multiple regression model that contained one binary predictor and one quantitative predictor and then went on to investigate such models more extensively. Although we primarily focused on models with a binary predictor, the methods and concepts extend readily to multiple regression models containing a general qualitative variable that, rather than defining just two groups, defines *c* groups.

We also learned how to formulate multiple regression models that contain "interaction effects" as a way to account for predictors that interact. We also investigated a special kind of model —called a "piecewise linear regression model" —that uses an interaction term as a way of creating a model that contains two or more different linear pieces.