Aim of the course:
The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.
Learning outcome, competences knowledge:
- knows the introductory theories of mathematics
- Interest for theoretical issues
- understanding literature that contains mathematical formulas and terminology
- using mathematical knowledge in building computer models (well, at least some, but the more the better).
Content of the course
Topics of the course
- probability theory
- linear algebra
- the basics of analysis, and differential equations, accompanied by examples of psychological and biological applications.
Learning activities, learning methods:
- Lectures and interactive discussions
- For numerical solutions when we need them, we will use Matlab or R-Studio.
Evaluation of outcomes
Learning requirements, mode of evaluation, criteria of evaluation:
- Reliable basic knowledge in the domain of mathematics mode of evaluation: examination and practical course mark
criteria of evaluation:
- Knowledge on basic concepts and the skill of utilizing the modells of the big mathematics topics
Crilly, T. (2007). 50 mathematical ideas you really need to know. London: Quercus.
Strang, G. (2009). Introduction to linear algebra. Wellesley, MA: Wellesley Cambridge Press
Holzner, S. (2008). Differential equations for dummies. New York: Wiley.