Quantitative research is a research strategy that focuses on the systematic collection and analysis of numerical data to test theories, examine relationships between variables, and draw generalizable conclusions. It is typically grounded in a deductive logic, where hypotheses are derived from theory and empirically tested using structured and standardized procedures. At its core, quantitative research aims to ensure objectivity, reliability, and validity in the investigation of socio-economic, psychological, and related phenomena.

Beyond statistical analysis, quantitative research fundamentally relies on the rigorous design of data collection processes. This includes the careful operationalization of constructs, the development or selection of measurement instruments, and the planning and implementation of studies in both laboratory and field settings. High-quality quantitative research therefore depends not only on statistical-analytical techniques but also on the quality and integrity of the data generation process. This course focuses on the latter.

The course starts with a (hybrid) kick-off session in which participants’ needs, expectations, and research interests are discussed. Based on this session, specific topics in quantitative research methodology are identified and assigned. Participants will then work individually or in pairs to prepare and lead a 60-minute session on their topic during the three-day block seminar in July. All sessions are expected to be grounded in current scientific literature.

The course addresses the quantitative research process, key aspects of research design (including experimental, quasi-experimental, and observational approaches), as well as the strengths and limitations of these designs. It further covers practical challenges in data collection (e.g., data quality) and common challenges of quantitative research, such as issues of measurement validity, sampling biases, and causal inference. In addition, principles of good scientific practice and research ethics are discussed, including transparency, reproducibility, and responsible data handling. The focus is on developing a deeper understanding of how high-quality quantitative data are generated in both laboratory and field contexts.

A distinctive feature of the course is its interactive and student-driven format: following the kick-off session, participants develop and lead their own sessions on selected topics, which are discussed collectively during the block seminar.

The course is designed for doctoral students and advanced master’s students with a strong interest in quantitative research. Initiative, creativity, and critical thinking are expected and encouraged. The course aims to support participants in advancing their own research projects by strengthening their methodological competence in quantitative research.

- Students gain an overview of the quantitative research process
- Students understand the logic, potentials, and limitations of quantitative research designs
- Students learn how to design and implement quantitative studies in laboratory and field settings
- Students develop a deeper understanding of measurement, operationalization, and data quality
- Students are able to identify and critically reflect on common biases and challenges in quantitative research
- Students become familiar with principles of good scientific practice and research ethics
- Students learn how to critically evaluate quantitative research and apply methodological knowledge to their own projects
- Students develop and present a research-based session on a selected topic in quantitative methodology

Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/evaluation/course-evaluation.html