In this chapter, we looked at using probabilistic linear models to predict a qualitative response with the two most common methods: logistic regression and discriminant analysis. Additionally, we began the process of using the ROC charts in order to explore the model selection visually and statistically. We also briefly discussed the model selection and trade-offs that you need to consider. In the future chapters, we will revisit the breast cancer dataset to see if we can improve our predictive ability with more complex techniques.