R Course Info

An introduction to R for policy analysis courses have been run in-person in 2019 and online in 2020 and 2022. Special thanks to those that shared their R Programming origin stories, including: Barbara Perry, Praveen Jayasuriya, Anya Cushnie Mills, Benjamin Osenius-eite and David Keyes.

The course has since been launched as a MOOC at PolicyAnalysisLab.com:

What’s Covered:

The introduction to R for policy analysis course typically runs for six weeks. The course covers practical aspects of using R for applied policy analysis, with the course covering the mechanics of importing, cleaning and analyzing data, and how to communicate your results. Concepts covered in the course include:

• The fundamentals of programming and R – which will cover just enough of the theory to get you doing cool stuff with R.
• Exploratory analysis – how to quickly understand the basics of a dataset and use programming to explore policy questions. 
• Data cleaning – which will show how we can work with, and clean messy, data to make it useful for analysis.
• Data visualization and presenting results – how to communicate your analysis through modern data visualization, graphics and statistical summaries.
• Automation and reproducibility – practical tips to use R programming to automate repetitive tasks and enhance reproducibility.

What’s Needed to Participate:  

• A willingness to learn and give us honest and open feedback (so we learn too!).
• At least one other person to work with to complete group activities in the course.
• A basic understanding of data analysis and computers (eg can use a formula in excel to calculate the average of something). 
• A computer with R and R studio installed (Mac, Windows or Linux).

What’s Not Needed to Participate:  

• Any programming experience: We’ll start from the basics and go from there
• A phd in applied mathematics: I don’t have one, so why should you?