This is the GitHub repository for the workshop series called Demystifying R and RStudio, given at the Children's Hospital of Philadelphia (CHOP) by Arcus Education.
Welcome to Demystifying R and RStudio!
This series is intended to be a gentle introduction to R and RStudio for people who interact with data and want to work in the R statistical programming language (or just understand what it is and why it matters). This course is geared towards beginners who are comfortable doing basic tasks with data that comes in rows and columns (for example, organizing data in Excel) but have no programming background.
The series will cover why and how to get started using the R statistical programming language in your work. We'll talk the definition of R (a programming language), RStudio (a software environment useful for working with the R language), how to access and use these tools, and next steps for learning how to use them. What we won't do is show you how to get started writing code or analyzing data using R. So if you just want to get an overall idea of what R and RStudio are all about, without actually doing hands-on coding, this is the perfect workshop series for you!
Material in later sessions does build on work done in earlier sessions, but don't let missing a session keep you away from attending later sessions. We try to overlap material to help keep everyone caught up!
Session 1: Introduction to R/RStudio
Content:
- R is a programming language created for statistical data analysis
- Why scripts? Reproducibility and open source data science
- RStudio is one way to work with R
- Considerations for working with R and RStudio at CHOP
- Posit.Cloud
Goals:
- Be able to describe the difference between R and RStudio
- Be able to give one advantage for using scripts written in R for data analysis
- Have a concrete next step for knowing how to get R and RStudio at CHOP
Session 2: Literate Statistical Programming
Content:
- Review of R and RStudio
- Literate programming is a programming paradigm
- Research reproducibility reminders
- Quarto documents
- Next steps
Goals:
- Describe what makes programming "literate"
- Explain the real-life consequence of irreproducible research
- Name one way Quarto documents can be helpful in data analysis
All of the material in this GitHub repository is copyrighted under the Creative Commons BY-SA 4.0 copyright to make the material easy to reuse. We encourage you to reuse it and adapt it for your own teaching as you like!