PhD / Postdoc / 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 www.crs.uzh.ch.

Participants 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.

Fabio Molo & Rachel Heyard

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

1 ECTS (has to be recognized by your faculty)

New conditions of participation:

• A no-show will lead to a blocked account and the cancellation of all other booked GRC courses.   
• You may only register for two courses per semester.

-> Further conditions