Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical regression. CART methods are frequently used in applications where it is difficult to specify an appropriate regression model explicitly. In this short course we will provide an overview of CART methods, apply these approaches to gain practical insight from data, demonstrate techniques to visualize predictions in the CART framework, and compare and contrast these methods with regression and other approaches. The goal is for students in this class to learn why, when, and how to use CART in their research. Students should have basic understanding of statistical principals and regression for this course. We will the R statistical programming package.