Whether during the coronavirus pandemic, in marketing or in classic online evaluations - statistical analyses play a major role in our everyday lives, as they have a direct or indirect influence on private, economic or even political decisions. This makes it all the more important to familiarise ourselves with the methods of causal inference in order to understand cause-and-effect relationships at their core.
Together with Prof Dr Martin Spindler, Dr Philipp Bach has therefore fundamentally revised a Bachelor’s lecture and exercise on causality at the University of Hamburg Business School and added fresh examples and practical tasks. After a successful pilot phase, which was initially only open to students of business administration, he has now opened the lecture to students of all other subjects at UHH. The motto: “Causal inference for everyone!”
The aim: to build up a basic understanding of causal inference by allowing students from all subjects to test the knowledge they have learnt with their own statistical analyses and by creating their own ‘data products’ that are as clear as possible.
The interdisciplinary teaching project “Causal Inference for All!” is now in its third round of funding from the Digital and Data Literacy in Teaching Lab (DDLitLab for short) and has evolved from a subject-specific to an interdisciplinary course. In the coming semester, the course will be expanded to include AI and machine learning and will remain open to all UHH students.