An ‘Introduction to R for Policy Analysis’ is designed for public policy professionals, consultants and researchers that want to harness the power of R in their work.
Reflecting the fact that the best way to learn how to use R is through deliberate practice, this course emphasizes application over theory. With a combination of practical exercises and ‘Simulation-Based Learning’ activities used when introducing concepts, tools and techniques throughout the course.
Topics covered during the course include:
- Setting up R, Rstudio and Swirl: providing a gentle introduction to getting everything set up, such as R, RStudio and packages from the ‘tidyverse’.
- The fundamentals of programming and R: just enough of the theory to get you started working with real data in R.
- Exploratory analysis: principles for exploring and analyzing data in the context of applied policy analysis.
- Data cleaning: illustrating how to identify (and correct) common errors and inconsistencies faced when working with real-world datasets.
- Data visualization: providing practical tips for effective data visualization and data storytelling.
- Automation and reproducibility: introducing practical tools for automating repetitive tasks and enhancing the reproducibility of your analysis.
This course is designed to provide a practical and beginner-friendly introduction to the R programming language for policy professionals, consultants and researchers. Topics covered in the course include data cleaning, exploratory analysis, data visualization, and tools for automating and streamlining analysis. Both functions from base R and the tidyverse packages are covered.
After successfully completing this course you should:
- Understand the ‘nuts-and-bolts’ of using the R programming language
- Be comfortable importing and working with data from a variety of formats (including data stored by data analysis and statistical software like Stata, SPSS, SAS and Microsoft Excel).
- Be armed with a useful set of conceptual tools and ‘rules of thumb’ for conducting policy analysis with real-world data.
- Build a solid base of understanding of how R can be useful at different stages of the applied policy analysis cycle.
- Grasp the principles of producing effective data visualizations with ggplot2 and what to think about when crafting a ‘data story’.
- See how R can help automate repetitive (and boring) tasks through the use of functions, loops and R’s apply functions.
Assessments administered throughout the course include a series of short quizzes, ‘find the error’ exercises (to get learners comfortable with reading and troubleshooting code), and hypothetical policy scenarios (that mimic the types of problems we often face in real-world policy analysis).
Learners will need to pass all assigned assessments to receive a course certificate.
This course is designed to introduce policy professionals, researchers and consultants to the R programming language. While prior experience with data analysis will be helpful, the course is targeted at public policy practitioners that have never used a programming language before. However, to get the most from this course, learners should:
- Be willing to practice: To get the most out of this course learners will need to get their hands dirty. This includes by completing the assigned problem sets and policy scenarios, replicating examples presented in course videos and taking part in discussions on the discussion forum.
- Have some familiarity with public policy and research: The course has been designed as an introduction to R for public policy professionals, not an introduction to public policy for programmers. As such, it’s assumed that learners will be familiar with the fundamentals of public policy.
- Hold a basic understanding of data analysis and computers: such as being able to use basic formulas in Microsoft Excel.
- Have access to a computer: with R and R studio installed (Mac, Windows or Linux).
Who is this course for?
This course is designed to introduce experienced public policy professionals, consultants and researchers to the R programming language. It is an introductory R programming course for public policy professionals, rather than a public policy course for programmers.
What will I learn by the end of this course?
This course is designed to provide a beginner-friendly and practical introduction to the R programming language. Topics covered in the course include data cleaning, exploratory analysis, data visualization, and tools for automating and streamlining analysis. Both functions from base R and the tidyverse family of packages are covered.
How long does the course take?
The course’s six modules are designed to be taken over a period of six weeks. Each module should take between three to seven hours to complete, depending on your familiarity with data analysis and programming.
Will I receive a course certificate?
Course certificates will be issued for learners that have completed the course and passed all assigned problem sets.
How long do I have to complete the course?
Although there are no strict deadlines, learners will have access to course material for a period of twelve weeks after registration.
