Universität Wien

400009 SE Experiments in the Social Sciences (2024S)

Methods seminar

5.00 ECTS (2.00 SWS), SPL 40 - Doktoratsstudium Sozialwissenschaften
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 05.03. 11:30 - 13:30 Seminarraum 12, Kolingasse 14-16, OG01
  • Tuesday 19.03. 11:30 - 13:30 Seminarraum 5, Währinger Straße 29 1.UG
  • Tuesday 09.04. 11:30 - 13:30 Seminarraum 11, Währinger Straße 29 2.OG
  • Tuesday 16.04. 11:30 - 13:30 Seminarraum 5, Währinger Straße 29 1.UG
  • Tuesday 23.04. 11:30 - 13:30 Seminarraum 2, Währinger Straße 29 1.UG
  • Tuesday 30.04. 11:30 - 13:30 Seminarraum 5, Währinger Straße 29 1.UG
  • Tuesday 07.05. 11:30 - 13:30 Seminarraum 2, Währinger Straße 29 1.UG
  • Tuesday 14.05. 11:30 - 13:30 Seminarraum 5, Währinger Straße 29 1.UG
  • Tuesday 21.05. 11:30 - 13:30 Seminarraum 11, Währinger Straße 29 2.OG
  • Tuesday 28.05. 11:30 - 13:30 Seminarraum 5, Währinger Straße 29 1.UG
  • Tuesday 04.06. 11:30 - 13:30 Seminarraum 11, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

The scientific experiment is a central way to advance knowledge in the empirical social sciences. By randomly assigning participants to experimental groups, experiments allow us to make claims regarding causality. Hence, if our aim is to establish causal inferences, wherever possible it is recommended to conduct experiments.
In this course we will discuss the scientific experiment, how and when it can be used, what pitfalls to avoid, and how to interpret results. We will focus on statistical power, design of stimuli, and open science (with a focus on Registered Reports). We will also focus on how best to analyze results.
We will explore these topics by reading and discussing texts, through inputs by me, short summaries of the texts presented by you, and hands-on analyses in R. Throughout, we will engage with your phd projects and your individual perspectives.
Each student will give a short summary of one of the papers we discuss. Everyone is expected to participate actively in the discussions.
In the hands-on part of the seminar, we will analyze actual data/experiments. We will use the software R. Although not needed, a basic understanding of R is recommended. If R is new, I recommend reading introductory texts or watching online tutorials. Here are some helpful materials:
- https://r4ds.had.co.nz
- https://github.com/jobreu/r-intro-gesis-2021
- https://github.com/ccs-amsterdam/r-course-material
- https://www.youtube.com/watch?v=BvKETZ6kr9Q
1. Introduction
2. Basics: What’s an Experiment?
3. Planning an Experiment
4. Experimental Designs
5. Open Science & Registered Reports
6. Statistical Power
7. Analysis: t-Tests
8. Analysis: ANOVAs
9. Analysis: Regressions
10. Analysis: Multilevel Analyses
11. Conclusion

Assessment and permitted materials

Everyone participates actively in the course. Willingness and openness to take part in the discussion are a prerequisite.
During the semester, everyone picks a text and gives a short presentation. The presentation needs to be in English.
Essay at the end, in which you present your phd project and an experiment you are planning to conduct. In case you are not actually planning to conduct an experiment, this will then be a hypothetical task. The essays are recommended to be in English. However, it is also possible to write an essay in German.

Minimum requirements and assessment criteria

Active participation
Presentation of text (50%)
Essay (50%)

Examination topics

Participants need to follow all presentations and what is being discussed. Participants also need to read all texts and prepare for the course

Reading list

ield, A. P., & Hole, G. (2003). How to design and report experiments. Sage publications Ltd.
• Gelman, A., Hill, J., & Vehtari, A. (2020). Regression and Other Stories (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781139161879

Association in the course directory

Last modified: We 31.07.2024 12:06