Module CAN6 - Advanced Statistical Methods
Master's degree program in Psychology: Cognitive Affective Neuroscience
Module coordinator:
Contents
The courses of the module offer a hands-on introduction to advanced statistical analysis methods and methods of cognitive computational modeling. The basis is an introduction to Matlab, a data-oriented programming environment, which is subsequently used to deal with the analysis methods for modeling. The seminar in the winter semester focuses on advanced statistical methods for data analysis (e.g. cluster analysis, PCA, ICA, advanced analysis of EEG data), which are applied in practical exercises. The focus of the seminar in the summer semester is on cognitive modeling methods (e.g. reaction time distribution models, differential equation models, neural networks), with participants gaining experience with these modeling methods themselves.
Winter semester
The Opal module for the winter semester will be activated shortly.
Summer semester
OPAL module for the summer semester 2020
Literature
The following literature is recommended to deepen the content presented in the lessons:
- Rosenbaum, D.A. (2015) Matlab for behavioral scientists. New York: Routledge.(Slub Online Version)
- Cohen, M.X. (2015) Analyzing neural time series data : theory and practice. Cambridge, MA: MIT Press.(Slub Online Version)
- Bortz, J, (2005) Statistics for social scientists. Heidelberg: Springer(Slub)
- Anderson, B. (2014) Computational neuroscience and cognitive modeling: a student's introduction to methods and procedures. Los Angeles: Sage.(Slub Online Version)
In-depth literature on specific topics of the lessons can be found here:
- WS: Supplementary literature Time-varying signals
- WS: Supplementary literature Multivariate methods
- SS: Supplementary literature
Further materials & Matlab license
Please note: this is a list of external resources to help you find further material and we have no control over their content.
- Introduction to Matlab (Screencast from the University of Edinburgh)
- Tutorial on Matlab (PDF by Antonia Hamilton, University College London)
- Matlab Cheat Sheet (PDF; one of many crisp command overviews)
- Information on the Matlab Campus license/reference for students
- GNU Octave (Open Source, compatible with Matlab)
- Matlab Onramp: Free introductory course including online Matlab to try out directly: (Attention: a free Mathworks account is required for this)
Tutorial
To support you in learning programming in Matlab, we offer a tutorial in which the exercises are discussed and your questions are answered.
Examination
The module examination consists of a written exam lasting 90 minutes at the end of the summer semester.