Research and Design
Full course description
The course provides an introduction to advanced statistical methods in psychological and management research. The course covers qualitative and quantitative methods. With regard to qualitative methods, the course provides an introduction to interview techniques, coding and rating of qualitative interview data, and the transformation of qualitative data into quantitative data. With regard to quantitative methods, the course covers mediation and moderation, moderated mediation and mediated moderation, and multi-level analyses. Furthermore, the course provides an introduction to methods of recruiting study participations (e.g., online surveys).
Specifically, the module seeks to provide students with skills in developing a good research design. Based on various papers discussing or presenting sophisticated and new research designs or methodological approaches, the students will learn to understand and how to use the following methods:
- Basic regression analyses and ANOVA
- Moderated mediation / mediated moderation
- Multi-level analyses (HLM)
- Growth modelling including dynamic mediated growth models and discontinuous growth models
- Combining field studies and experiments
- Diary studies and experience sampling methods
Generally, students will improve and gain substantial knowledge in psychological and management research methods. Students will be provided with knowledge on the latest advances and foundations in quantitative and qualitative psychological methodology. Students will learn how to present methodological approaches, research designs, and findings in class. They will thus learn to develop, apply, and report the findings of a particular design/method. The main focus of the module is on a general understanding and the application of the methodological approaches.
The students will form groups and deal with one methodological approach/design in detail. They will conduct a mini-project to understand how to apply the design in practice. Thus, students will learn social competencies in small group interactions and improve their teamwork- and presentation skills. Students will also be provided with self- and time-management skills in order to handle significant workload.
Basic knowledge in descriptive and inferential statistics is required.