About This Course

The module “Good Statistical Practice” introduces students to the specific concepts of research integrity that are related to the practice of statistics. This includes ethical principles of statistical practice, reproducibility, good written, visual and oral communication, good computational practice and computational efficiency. Besides theoretical insights into the foundations of statistical practice students acquire practical skills using modern computational tools (e.g. dynamic reporting, version control, containerization), they practice effective presentations and report writing of statistical results and they start to learn about general programming techniques (e.g. unit tests, debugging, job scripting, parallelization).

The module provides insights and practical tools that are useful throughout the curriculum of the master program in biostatistics or other programs focused on quantitative research. It is taught in a flipped classroom setting: students are required to learn about concepts using provided material and complete assignments before an in-person session. Assignments and the in-person session contain peer and staff feedback and assessment.