Date(s) - 09/28/2017
1:30 pm - 4:00 pm
Category No Categories
A reproducibility study in psychology found that only 39 of 100 studies could be reproduced – a serious limitation to advancing social science research. But the emergence of R as the prime software for data science and its adoption in computer science has rapidly created new paradigms of documentation and collaboration. This workshop helps you learn R Markdown and Git – two important tools to produce easy and consistent documentation of your analysis and provide a scalable platform for data sharing, version control and collaboration.
Topics: R Markdown and Bookdown. Introduction to Git
- Anderson, B. (2017). Week 5 Slides: Reproducible Research. R Programming for Research Course.
- R Studio (2016). RMarkdown Cheatsheet.
- Wickham, H. (2015). Git and Github. R Packages.
- RStudio RMarkdown Lessons.
- Grolemund G., & Wickham, H. (2017). RMarkdown. R for Data Science.
- Grolemund G., & Wickham, H. (2017). RMarkdown Formats. R for Data Science.
- Bryan, J. (2017). STAT545 Course 1 Slides.
- Bryan, J. (2017). Happy with Git and GitHub for the useR.
Instructor: Ryan Wesslen
Pre-Requisites – Follow our pre-requisites guide
Also, please visit and confirm software requirements for this workshop
Registrations are closed for this event.