Reproducible Research Reports with R Markdown with Daisy Huang, Research Computing Bootcamp

Wed, Jan 20, 2021, 12:30 pm
Center for Statistics and Machine Learning
Princeton Institute for Computational Science & Engineering (PICSciE) and OIT Research Computing

Full event details and registration link here.

Do you use LaTeX or Microsoft Word to write your analysis report? Have you ever wished that all your research results (e.g., data analysis, graphs, result discussions) can be included in one place and can be updated effortlessly? Are you tired of all the copying and pasting that you have to do between R and LaTeX/Microsoft Word?

Rmarkdown provides a seamless workflow between data processing, analysis, and presentation. Analysis results in a report can be updated in a snap. Your report format can be switched between different common formats (e.g., pdf, html, Microsoft Word) in no time. Your R experience cannot be complete without knowing the Rmarkdown package!

Learning objectives

By the end of the session, participants should be able to create their own Rmarkdown reports.

Knowledge prerequisites

Participants should have at least basic familiarity with R and RStudio – this session is notappropriate for people with no prior R experience.

Hardware/software prerequisites

This session is heavily hands-on. To follow along with the exercises, participants should have both R and RStudio installed on their laptops. Instructions for how to do this can be found on the advance setup guide for PICSciE virtual workshops. Ideally, participants will also have installed the Rmarkdown package in advance.

Alternately, participants who prefer to run RStudio remotely on one of Princeton’s systems can do so via the “myadroit” web interface to the Adroit cluster. To do so, you should first register for an account on Adroit, as described in the advance setup guide for PICSciE virtual workshops. Then, connect to “myadroit” and start a MATLAB session, as described here.

Session format

Presentation, demo, and hands-on