Whether you new to R or have been using it for years, chances are your data analysis workflows could benefit from the use of custom R packages. R packages provide a consistent and effective means of organizing your projects, ensuring reproducibility, and sharing your research. In this workshop you will learn both how to create your own packages from scratch (complete with functions, scripts, markdown files, raw data, processed data, PDFs, images, and more), and how to share your packaged research products with colleagues locally, and through github. With a but a few lines of code you too can reproduce a complete project framework, package and share an entire semester's worth of course materials, or provide a potential employer with your latest and greatest R code.

Prerequisites: Introductory R. This workshop will not cover the basics to command line R or script management. Advanced knowledge of R is not required.

Software Used: R, RStudio, GitHub

Topics

This workshop covers:

• Creating packages from scratch
• Sharing packages through GitHub
• Creating packages for reproducible research

During this Workshop

Participants will be able to download materials for the workshop and are encouraged to listen, practice, and interact as it suits their learning style.

This session is designed in a follow-along format with instructional staff available for help.

Preparing for this Workshop

This workshop is designed for attendees who have the following:

• a Yale NetID to use lab machines or personal computer with software installed
• basic experience with the Windows OS (if using a lab computer)
• Introductory R experience

In order to provide the best learning experience possible, we ask that you arrive before the scheduled start-time of the workshop. Arriving more than 5 minutes late may make it difficult to catch up with the other participants.

Please email statlab@yale.edu with any questions about this workshop.