Foundations of R
Tour of R and RStudio
Further reading
Main types of objects in R
Further reading
Names and factors
Further reading
Subsetting
Further reading
Quiz
Quiz 1
100 attempts allowed
Practical 1
Solution
Importing and exporting data
Further reading
Exploring data
Further reading
Cleaning data
Further reading
Quiz
Quiz 2
100 attempts allowed
Practical 2
Solution
Efficient data handling with tidyverse
Selecting and arranging cases and columns
Further reading
Merging data
Further reading
Recoding variables
Further reading
Exploring data with summaries and tables
Further reading
Quiz
Quiz 3
100 attempts allowed
Practical 3
Solution
Visualizing data
Basics of ggplot
Further reading
Facets and geoms
Further reading
Statistical transformations
Further reading
Visualising factors
Further reading
Formatting graphs
Further reading
Doing descriptives using weights
Further reading
Quiz
Quiz 4
100 attempts allowed
Practical 4
Solution
Analysing data in R
T tests and Chi-square
Further reading
Correlation and regression
Further reading
Quiz
Quiz 5
100 attempts allowed
Practical 5
Solution
Make the course better
References
Introduction to R for Social Researchers
A Practical Course on Data Preparation, Visualisation, and Statistical Analysis
Learn how to use R confidently for real social research. This hands-on course guides you through data preparation, visualisation, and core statistical methods using practical, research-driven examples. Build a solid R workflow you can immediately apply to your own data.
Minimum price
$200.00
$200.00
You pay
$200.00Author earns
$160.00About
About the Course
Introduction to R for Social Researchers is a practical, step-by-step course designed to help social researchers confidently use R for real research. The focus is not on programming for its own sake, but on building a solid, usable workflow for working with social science data.
The course includes over 6 hours of video content, combining clear explanations with live demonstrations in R and RStudio. It takes you from first contact with R through the core skills needed for everyday research: preparing and cleaning data, working efficiently with R, creating clear, publication-ready visualisations, and carrying out common statistical procedures used in social research. Throughout, the emphasis is on both how to do things in R and why they are done that way in applied research settings.
Rather than abstract or toy examples, the course is grounded in realistic, real-world data familiar to social researchers, including large survey datasets and complex sample designs. Each section is accompanied by hands-on practical exercises, with worked solutions, so you can actively practise the skills and check your understanding as you go.
In addition to the videos and practicals, the course provides access to a dedicated discussion forum, where you can ask questions, clarify concepts, and get help when applying the material to your own data. This support is designed to help you move beyond passive learning and build genuine confidence in using R independently.
This course is well suited for:
- PhD students and early-career researchers
- Social scientists transitioning to R from SPSS, Stata, or Excel
- Policy, education, and applied researchers who need a modern data workflow
- Anyone who wants a clear, structured foundation before moving on to more advanced methods
By the end of the course, you will be able to work comfortably in R, understand the logic of modern R workflows, and apply R effectively to your own social research projects, using tools and practices that scale beyond this course.
This course is included in these 2 tracks...
Categories
Instructor
About the Instructor
Alexandru Cernat
Alexandru Cernat is a professor in the social statistics department at the University of Manchester. He has a PhD in survey methodology from the University of Essex and was a post-doc at the National Centre for Research Methods and the Cathie Marsh Institute. His research and teaching focus on: survey methodology, longitudinal data, measurement error, latent variable modelling, new forms of data and missing data. He am also the founder of longitudinalanalysis.com, a platform that helps researchers and analysts learn to collect, clean, and analyse longitudinal data. You can find out more about him and his research at: alexcernat.com.
Episode 267
An Interview with Alexandru Cernat
Material
Course Material
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