Data analysis

The course provides knowledge and skills in scientific data analysis relevant to the fields of psychology and cognitive science. The main aim is to prepare students for independent research by developing their ability to select, apply, interpret, and critically evaluate both quantitative and qualitative methods.  The quantitative part of the course introduces central concepts in descriptive and inferential statistics where inferential statistics are in focus, with examples of commonly used techniques for analyzing relationships and differences between variables. Students are also introduced to key practices in data preparation, assumption testing, and interpretation and reporting of results according to scientific standards. Selected topics related to the evaluation of psychological measurements are included.  The qualitative part of the course covers fundamental approaches to the analysis of data. Students practice techniques for coding, identifying patterns, and interpreting qualitative material, while considering quality criteria such as credibility, transparency, and reflexivity.  The course emphasizes an active learning model where students engage in problem-solving, analysis, and critical discussion, both individually and in groups. Teaching activities such as lectures, supervised exercises, and seminars support the development of methodological understanding and analytical skills. Supervision is offered throughout the course to guide students in their work.