ABSTRACT
In this chapter, the authors demonstrate alternative approaches. Three general guiding principles that motivate what the people learn here are be systematic when organizing their filesystem, automate when possible, and minimize the use of the mouse. A typical data analysis challenge may involve several parts, each involving several data files, including files containing the scripts the people use to analyze data. In this chapter, the authors introduce the people to the version control system Git, which is a powerful tool for keeping track of these changes. Finally, the people learn to write reports in R markdown, which permits them to incorporate text and code into a single document. They will demonstrate how, using the knitr package, they can write reproducible and aesthetically pleasing reports by running the analysis and generating the report simultaneously.
