SUBJECT

Statistics and Methodology

CCNM17-107

seminar

Master

Faculty of Education and Psychology

Cognitive Science MSc

Computational and Cognitive Neuroscience MSc

4

Semester 1

Autumn semester

The course starts with an introduction of basic concepts of statistics (distributions and estimation of distribution parameters; hypothesis testing, types of errors, significance, power, and effect size), and continues with methods of univariate statistics (correlation and regression; comparing two or more means; between-subject and within-subject designs; non-parametric methods). Depending on the audience, we can also address more complex methods such as multiple regression, analysis of covariance, MANOVA, and exploratory factor analysis. For carrying out statistical tests we use SPSS and R-Studio.

Learning outcome, competences knowledge:

• use SPSS and R-Studio

attitude:

• More open to the explorative and conceptual analysis
• Statistics is understandable and can be used creatively

skills:

• Flexible data analysis with spreadsheet
• Finding new (and old but unused) methods

Content of the course Topics of the course

• distributions and estimation of distribution parameters;
• hypothesis testing,
• types of errors,
• significance, power,
• effect size
• correlation and regression;
• comparing two or more means;
• between-subject and within-subject designs;
• non-parametric methods

Learning activities, learning methods:

Lectures and interactive discussions

Evaluation of outcomes
Learning requirements, mode of evaluation, criteria of evaluation:
requirements

• Data analysis methods
• Summarizing the methodological literature

mode of evaluation: short exams and project work

Coolican, H. (2014). Research Methods in Statistics and Psychology. London: Psychology Press