This course provides a hands-on introduction to statistical methods for causal inference. Over two weeks, students are introduced to experimental and quasi-experimental methods which allow them to infer cause-and-effect relationships robustly. We teach these methods from both a theoretical and applied lens, supplementing lectures with hands-on computer tutorials in the R programming language to help students learn by doing.
Please note: final course details, dates, and tuition fees for the Summer 2027 programme will be published on this website by the end of November.
Course overview
- Course dates: TBA for 2027
- Attendance: In-person
- Forms of tuition: Lectures and computer tutorials
- Forms of assessment: Quizzes, presentation, take-home assignment
- See the course curriculum
Course level
- Level: Master's
- English language requirement: B2 level or higher (equivalent to IELTS 6.5)
- See the entry requirements
Workload
- Credits: Equivalent to 3 ECTS
- Contact hours: 45
- Self-study hours: 15
Lecturers
- Dr. Sanchayan Banerjee & Jack Fitzgerald
- Faculty: Faculty of Science (BETA), IVM