This project explores the question: What demographic and situational factors are common among people who commit homicide in the United States? And can those factors be used to identify offender types or predict how a crime is committed? The goal is to use clustering and logistic regression in order to uncover meaningful patterns in homicide offender behavior. All visualizations were created using base R and the ggplot2 package.

An informational presentation about the differences between correlation and causation in statistics.