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80560-01 - Vorlesung: Scientific Reasoning in Empirical Research (2 KP)
| Semester | Herbstsemester 2026 |
| Angebotsmuster | unregelmässig |
| Dozierende | Dan Raphael Schley (danraphael.schley@unibas.ch, BeurteilerIn) |
| Inhalt | Course summary This course introduces students to core ideas in measurement, experimentation, and causal inference, while treating them as parts of a broader problem in the philosophy of science: how researchers move from observable data to defensible conclusions about latent constructs, interventions, and causal processes. It is designed for both business school and economics students. Students who are new to these areas will be introduced to the major concepts and tools. Students who have already encountered one or more of these traditions will learn how to think critically about the assumptions that make any given approach persuasive, and how to choose methods that are appropriate to the substantive problem at hand. Content This course examines measurement, experimentation, and causal inference as connected stages of scientific reasoning rather than as separate methodological topics. Its central concern is not only how particular tools are used, but why they work when they work, what assumptions they require, what kinds of inferential problems they can solve, and where their limits lie. In this sense, the course is explicitly oriented toward the philosophy of science, while remaining grounded in practical empirical research. The course is designed to be useful for both business school students and economics students. For business school students, it provides a framework for thinking more rigorously about constructs, surveys, experiments, field interventions, and the interpretation of empirical findings in areas such as management, marketing, and organizational research. For economics students, it provides a framework for thinking more rigorously about identification, exogeneity, observational data, and the assumptions required to move from statistical patterns to causal conclusions. By bringing these traditions together, the course helps students see where their training overlaps, where it differs, and how methodological choices should be driven by the research problem rather than by disciplinary habit. Across three modules, students are introduced to the foundations of measurement and psychometrics, to the logic of null hypothesis testing and experimental design, and to major approaches to causal inference in both experimental and observational settings. Students without prior exposure to these traditions will gain an introduction to the core concepts and practical vocabulary of each area. Students with prior methodological training will use the course to deepen their understanding of the assumptions beneath familiar tools and to develop a broader framework for evaluating when a given tool is well matched to a given research problem. A major aim of the course is to train students to identify tacit assumptions that often remain unspoken in published work. By the end of the course, students should be able to read a study and ask: What exactly is being measured? What assumptions justify the claim that treatment is exogenous? What assumptions are needed to move from observed patterns to causal conclusions? Which alternative interpretations remain open? Framed this way, the course does not merely teach methods. It teaches disciplined scientific judgment. Assessment is based on a final reviewer-style project. Each student will act as a reviewer of their own research project. Students who do not have an existing project will be given one. In this assignment, students are asked to evaluate the inferential structure of the project rather than simply report results. They must assess the assumptions built into the project’s measures, evaluate any tools used to justify exogeneity or rule out alternative explanations, and analyze the assumptions required to derive causal conclusions. The aim is for students to demonstrate that they can think like a critical scientific reviewer: identifying what a project assumes, what those assumptions permit the researcher to conclude, and where important inferential vulnerabilities remain. This assessment is designed to align with the central goal of the course, namely to cultivate disciplined judgment about measurement, exogeneity, and causality. |
| Lernziele | By the end of the course, students should be able to: • explain how measurement, experimentation, and causal inference fit together as linked stages of scientific inference • understand core concepts and tools from each module, including foundational ideas in psychometrics, experimental design, and causal inference • identify the explicit and tacit assumptions required by different empirical methods • evaluate whether a measure, design, or inferential strategy is appropriate for a particular research problem • distinguish between statistical evidence and causal interpretation • assess the credibility of claims about constructs, exogeneity, and causality in published research • articulate how weaknesses in measurement can undermine testing, and how weaknesses in design can undermine causal interpretation • adopt the perspective of a critical reviewer who can diagnose what a study assumes, what it shows, and what it does not show |
| Teilnahmevoraussetzungen | No specialized mastery of all methods covered in the course is required at entry, but students should be comfortable with the basic language of empirical research, including variables, hypotheses, common forms of validity, and standard statistical reasoning. Students who already know some of the relevant tools will use the course to deepen and reorganize that knowledge at a more conceptual level. Students with less prior exposure will be introduced to the foundational tools and concepts as part of the course. The emphasis throughout is on understanding how methods depend on assumptions and how methodological choices should follow from the underlying research question. |
| Anmeldung zur Lehrveranstaltung | Please register for the course and the subsequent assignment by email to the Graduate School (gsbe-wwz@unibas.ch) no later than 18.08.2026. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| unregelmässig | Siehe Einzeltermine | ||
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Donnerstag 20.08.2026 | 09.00-12.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32 |
| Donnerstag 20.08.2026 | 14.00-17.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32 |
| Freitag 21.08.2026 | 14.00-17.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S14 HG.32 |
| Module |
Modul: Fachlich-methodische Ausbildung (Promotionsfach: Wirtschaftswissenschaften) |
| Prüfung | Leistungsnachweis |
| Hinweise zur Prüfung | Assessment is based on a final reviewer-style project. Each student will act as a reviewer of their own research project. Students who do not have an existing project will be given one. In this assignment, students are asked to evaluate the inferential structure of the project rather than simply report results. They must assess the assumptions built into the project’s measures, evaluate any tools used to justify exogeneity or rule out alternative explanations, and analyze the assumptions required to derive causal conclusions. The aim is for students to demonstrate that they can think like a critical scientific reviewer: identifying what a project assumes, what those assumptions permit the researcher to conclude, and where important inferential vulnerabilities remain. This assessment is designed to align with the central goal of the course, namely to cultivate disciplined judgment about measurement, exogeneity, and causality. |
| An-/Abmeldung zur Prüfung | An- und Abmelden: Dozierende |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |