Teaching Statistics in Health Sciences: The Potential of Simulations in Public Health

Abstract

This paper is a collection of thoughts from multiple discussions about the importance of appreciating and embracing statistical thinking in public health research and education. We think that statistical simulations can play an important role in fostering statistical reasoning in public health and that they can be a great didactic tool for students to generate and learn from data. Two main points are of relevance here. First, simulations can foster critical thinking and improve our reasoning about public health problems by going from theoretical thoughts to practical implementation of designing a computer experiment. Second, simulations can support researchers and their students to better understand statistical concepts used when describing and analysing population health in terms of distributions. Overall, we advocate for the use of more simulations in public health research and education to strengthen statistical reasoning when studying the health of populations.

Additional information

Notes on contributors

Robert Thiesmeier

Robert Thiesmeier is a PhD student in medical sciences at Karolinska Institutet in Stockholm, Sweden. Thiesmeier’s PhD focuses on a simulation-based approach for the design, analysis, and interpretation of individual participant data meta-analyses.

Nicola Orsini

Nicola Orsini is a principal researcher in biostatistics and associate professor of medical statistics at Karolinska Institutet, where he leads multiple courses on biostatistics for master’s and doctoral students in medical sciences and public health.