November 07-11, 2022
Welcome to the git repository of the Action Cognition and Computation Course
Objectives: Introduce fundamental tools for data analysis for different sources of data e.g. behavioral, eye-tracking, EEG data. Main focus will be on data exploration through plotting, hypothesis generation, and hypothesis testing.
Tools: pandas, numpy, python-MNE for analysis. matplotlib, seaborn for data visualization.
| Day | Take Away | Exercises |
|---|---|---|
| Day 1 | Data exploration | basics of plotting |
| Day 2 | Data wrangling | Behavioral data, Hypothesis testing with ANOVAs |
| Day 3 | Data cleaning | Eye-tracking data, outlier detection |
| Day 4 | Simulating data - I | EEG data, Fourier transform, |
| Day 5 | Simulating data - II | Parametric and Non-Parametric hypothesis testing |
This course is a work in progress. If you find any mistakes or have suggestions, please add them to the issue tracker.
I plan to add video lectures in the notebooks soon, so it's accessible to everyone!
I would like to thank Anne Lang, Franca Boße and Moritz Bammel for helping with the great content and Peter König for his guidance. Finally, I'm grateful for the funding provided by the Max Planck School of Cognition to complete the project.
This project is licensed under
