Statistical Computing

A practical introduction to statistical programming focusing on the R programming language. Students will engage with the programming challenges inherent in the various stages of modern statistical analyses including everything from data collection/aggregation/cleaning to visualization and exploratory analysis to statistical model building and evaluation. This course places an emphasis on modern approaches/best practices for programming including source control, collaborative coding, literate and reproducible programming, and distributed and multicore computing. Prerequisite: Statistical Science 210 and Statistical Science 240L or 230 or 231.