
STATISTICS FOR BRAIN AND COGNITIVE SCIENCES
Prerequisites:

Probability, random variables, descriptive and inferential statistics, confidence intervals, ttests, Ftests, basic issues in experimental design. The students can easily find materials on Internet (e.g. a comprehensive list of prerequisites is provided by the course of Statistical Methods in Brain and Cognitive Science on the MIT website). 
Examination methods:

Type of examination: Written and possible oral test.
Written examination: Open questions. 
Course unit contents:

Matrix Algebra (an introduction). Simple Linear Regression: An algebraic and geometrical approach. Linear Models: Simple and Multiple Regression, Regression with Dummy Variables, ANOVA for Factorial Designs, Repeated Measures ANOVA, Analyses of Covariance, Contrasts and Multiple Comparisons. Generalized Linear Models (an introduction). Moreover, upon completion of the course the students should also be experienced in the use of the R Packages. 

