Gruppe 1:
Why do we learn a lot from some graphs and nothing from others? How to communicate complex data effectively? Do we need to know how human perception works in order to represent experimental findings efficiently? What forms of visualization and what rules of visual communication to choose for our own research (e.g., in a master's thesis)?
This course is an introduction to the theoretical foundations of effective visual data communication from the perspective of perceptual psychology. The sessions will consist of theoretical and practical parts. The theoretical parts will provide an introduction to the purposes, possibilities, and problems of data visualization. We will discuss ideas from perceptual psychology that are directly related to successful data representation. In the practical part, students will apply what they have learned to their own projects. To do this, we will work with example datasets and/or students’ own data. Prior knowledge is not required, but students should be prepared to learn programming languages or data visualization tools.
Gruppe 2:
Insight into models, Experiments, and Methods in a selected topic in Cognitive Neuroscience, using e.g.
- Analysis of large data sets (PCA, Bayes factors, modeling, correlations, Procrustes analysis)
- Eye-Tracking
- Psychophysics
- Data visualization
- Peripheral physiology
- Cognitive Modeling
PC: Research-focused skills in the scientific and diagnostic process in cognitive neuroscience: Planning, conducting, and analysis of a psychological study. |
