This is my final project for IDS 702: Modeling and Representation of Data at Duke University. This course covered a broad variety of statistical models including hierarchial models, decision trees, and simpler techniques such as regression and hypothesis testing. For my project, I chose to use R to build a logistic regression model that predicts if patients have heart perfusion abnormalities. Prediction of such abnormalities could lead to reduced costs associated with testing and better health outcomes for patients. The project code can be found here, and a pdf of the final report is located here.