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Graduate Campus

Good Research Practice



Good research practices are of great importance for early-career researchers to foster rigorous research and tackle issues related to reproducibility. In this two-day course relevant topics are covered such as causes of irreproducible research, exploratory vs. confirmatory research, study design, open science, preregistration, reproducibility and replicability in experiments, reporting guidelines, writing statistical analysis plans, issues with small study research, and avoiding statistical pitfalls. We will provide solutions to support daily research practice, with workshops about the Open Science Framework (OSF), study registration, computational notebooks and pitfalls in statistical significance testing. For further information on reproducibility, visit

Course objectives

At the end of the course, participants will know:

  • What the major causes of irreproducible research are;
  • Best practices in planning and design of studies;
  • Documentation of research output with the Open Science Framework (OSF); 
  • Study protocols and preregistration;
  • The difference between reproducibility and replicability;
  • Statistical analysis plans and reporting guidelines;
  • Best practice data analysis: computational notebooks (R Notebooks);
  • How to avoid common statistical pitfalls.

Dr. Rachel Heyard, Dr. Eva Furrer & Prof. Dr. Leonhard Held Center for Reproducible Science (CRS), University of Zurich.

Target participants

This course is primarily aimed at PhD candidates and postdoctoral researchers in the empirical sciences. Knowledge of the R programming language is an advantage.


15 March 2024 9:00 - 17:00h

22 March 2024 9:00 - 17:00h



ECTS credit (PhD)  1 ECTS credit (has to be recognized by your faculty)