Introduction to R for Social Researchers

Introduction to R for Social Researchers is a practical course that will help you use R for real research. Rather than focusing on programming for its own sake, the course emphasises building robust, reproducible workflows for social science research, with a particular focus on data wrangling and data visualisation in R.

Learning outcomes

• Understanding the logic of R, including the main types of objects used in data analysis.
• Import and export data from common file formats used in social research.
• Apply data wrangling in R, including selecting variables, merging datasets, and recoding variables.
• Develop proficiency in data visualisation in R, using ggplot, facets, and appropriate statistical transformations.
• Create weighted summaries and visualisations for data arising from complex survey designs.
• Carry out core statistical analyses in R, including descriptive statistics, t-tests, chi-square tests, correlations, and regression models.

By the end of the course, you will be able to work comfortably in R and apply these skills directly to your own research projects.

Learning methods

The course combines over six hours of video content with hands-on practical exercises, using clear explanations and video demonstrations in R and RStudio. Learning is grounded in realistic, real-world survey data, including the European Social Survey.

Additionally, each section includes quizzes, practical exercises with worked solutions, and access to a dedicated discussion forum where you can ask questions, clarify concepts, and receive support as you apply the material to your own data.

Who this course is for

This course is for PhD students and early-career researchers who want to develop practical and transferable skills in R. Moreover, it is particularly appropriate for social scientists transitioning from SPSS, Stata, or Excel, as well as for policy, education, and other applied researchers who need modern, transparent, and reproducible data workflows. By focusing on core research tasks—data wrangling, data visualisation, and statistical analysis—the course provides a strong foundation for working with complex social data. It also prepares you to progress to more advanced topics, such as mediation and moderation analysis.

Testimonials

Thoroughly recommend anything taught by Alex.

Michelle Degli Esposti, Postdoctoral Researcher, University of Oxford

I owe Alex’s 2018 course my ‘re-birth’ as an R data manager and analyst.

Teresio Poggio, Research Assistant, University of Trento