The ability to quickly and efficiently read, manipulate, and analyze large real-world datasets has become a basic business skill. In this course we use R to explore the basic elements of data management, exploration, and statistical analysis. Specific topics include data acquisition and cleaning; subsetting, filtering, summaries; long and wide formats; data normalization; multi-table operations; accessing SQL data; visualization; basic statistical analysis; the use of simulation in data analysis; machine learning; and reporting. We will emphasize the use of the R packages `dplyr` for data manipulation and `ggplot` for visualization. Classes will involve a blend of lecture and in-class problem solving. Grading will be based on individual homeworks and a final project, which can be done in a group. No previous experience with R is assumed. With assent of the instructor, students may use their own data sets for the final project.