| Dozent/in |
Dr. Andrea De Angelis |
| Veranstaltungsart |
Masterseminar |
| Code |
FS211278 |
| Semester |
Frühjahrssemester 2021 |
| Durchführender Fachbereich |
Politikwissenschaft |
| Studienstufe |
Bachelor
Master |
| Termin/e |
Mi, 24.02.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 03.03.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 10.03.2021, 16:15 - 18:00 Uhr, 4.B54
Mi, 17.03.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 24.03.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 31.03.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 14.04.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 21.04.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 28.04.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 05.05.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 12.05.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 19.05.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 26.05.2021, 16:15 - 18:00 Uhr, 4.B02
Mi, 02.06.2021, 16:15 - 18:00 Uhr, 4.B02 |
| Umfang |
2 Semesterwochenstunden |
| Turnus |
wöchentlich |
| Inhalt |
Most students are keen on developing an empirical project for their Bachelor’s and Master’s theses. However, even when they possess some knowledge in methodology and statistics, they can meet more advanced problems, such as dealing with bounded dependent variables or designing an identification strategy to assess causal effects. Furthermore, students often lack the practical side of empirical research work, and may easily stumble in practical inconveniences, wasting precious time, and getting stressed. At the same time, recent evidence shows that results from published scientific papers, in many cases, fail to be replicated. Such “replication crisis” is a serious flaw for the advancement of science and causes growing mistrust towards scientific research. This second module of quantitative research design brings together these two problems, using the replication of real published papers as a learning opportunity for students willing to become proficient in quantitative research methods. Overall, the seminar introduces some more advanced research problems, such as: using regression modelling for making prediction, using simulations for taking good design and sample size decisions, dealing with bounded dependent variables, and identifying causal effects in experimental and non-experimental settings. In doing so, students will be guided and supported by the instructor to actively replicate real scientific results using those methods. The solution is thus to learn while supporting science. The seminar is intended for students with some basic knowledge in quantitative methods and R programming. Students will receive some of the most useful skills and tips for doing applied empirical analysis, including elements of research design, R coding and data literacy, effective writing skills, and presentation skills. Thus, while training students to tackle their future research tasks, this seminar will also bolster their ability to understand and produce empirical research. Students wishing to receive credits are expected to: study the weekly readings, solve the class exercises, and replicate a scientific paper working solo or in small groups. Motivated students are encouraged to write a replication seminar paper and to submit it to the https://projects.iq.harvard.edu/psreplication/about-psri, in order to gain an official DOI identifier for their work.
|
| Lernziele |
Research design, analyutical and statistical skills, data literacy. |
| Sprache |
Englisch |
| Begrenzung |
Descriptive statistics, linear regression, basic R programming |
| Anmeldung |
Research-Masterseminar; Open for advanced BA-students |
| Abschlussform / Credits |
aktive Teilnahme/Referat/Essay (benotet) / 4 Credits
|
| Hinweise |
Studienschwerpunkte: Politische Kommunikation/Vergleichende Politikwissenschaft/Internationale Beziehungen |
| Hörer-/innen |
Nach Vereinbarung |
| Kontakt |
andrea.deangelis@unilu.ch |
| Material |
Pflichtlektüre und Seminarmaterialien zugänglich auf Online-Plattform OLAT und Perusall.com |