Advanced statistics 2401-CS-11-AS-s2

This course introduces students of cognitive science to the principles and practice of quantitative data analysis using IBM SPSS Statistics. The focus is on developing both conceptual understanding of statistical methods and practical skills in applying them to real research problems in cognitive science. Students will learn how to summarize data, test hypotheses, explore relationships between variables, and build predictive models.
The course covers a range of fundamental techniques, including descriptive statistics, hypothesis testing (parametric and nonparametric), correlation analysis, clustering methods, linear regression, factor analysis, and decision tree models. Special attention is given to the interpretation of statistical results, their assumptions, and their application in cognitive and behavioral research.
Classes combine lectures, software demonstrations, and hands-on exercises. Students will regularly work with datasets, conduct analyses in SPSS, and interpret their results in a research-oriented context. By the end of the course, participants will be able to critically evaluate statistical findings in the literature and apply appropriate statistical tools in their own projects.
Learning outcomes:
1. Understand the role of statistical analysis in cognitive science research.
2. Correctly select statistical tests according to measurement levels and data assumptions.
3. Perform hypothesis testing, regression, clustering, factor analysis, and classification models in SPSS.
4. Interpret statistical outputs and report results according to academic standards.
5. Apply quantitative methods to analyze cognitive and behavioral data.