

This workshop is intended for people who have limited to no experience with preregistration, but who would like to learn more about it and how to implement it in their daily workflow. Preregistering your research can help you to think about your design, hypothesis, analyses and exclusion criteria before executing the research, which can prevent errors and make your workflow more efficient. Additionally, preregistration can make your research more trustworthy and transparent.
Open Science practices are transforming how research is conducted, emphasizing transparency, reproducibility, and collaboration. In this hands-on workshop, you’ll learn how to build a fully reproducible workflow for writing and publishing a scientific manuscript that integrates text, data, and code.
This workshop will introduce you to running power analysis simulations in R. By the end, you’ll learn what statistical power means in the null-hypothesis significance testing framework and how to perform such a power analysis for a class of models commonly used in cognitive psychology, linear mixed models.
This workshop will introduce you to running PsychoPy experiments online or locally. By the end, you’ll be able to use PsychoPy to flexibly design your own experiments for both online and in-person testing. Additionally, for in-person experiments, we’ll demonstrate how to get started with integrating eye tracking into your tasks.