Universität Wien

210112 UE M2: Research Methods for Political Science quantitatively (2022S)

(engl.)

8.00 ECTS (4.00 SWS), SPL 21 - Politikwissenschaft
Prüfungsimmanente Lehrveranstaltung

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Details

max. 35 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 10.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 17.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 24.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 31.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 07.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 28.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 05.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 12.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 19.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 02.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 09.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 23.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
  • Donnerstag 30.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course deals with the development of a research design. For this purpose all key concepts and steps of the research design are discussed: formulation of a research question, literature review, theory, hypothesis definition and testing, concept definitions and operationalization, case selection and empirical verification.
Some of the questions that will be discussed include the following: How do I find a research question? How to formulate a research question? What elements should a quantitative research design include? How can a research question be adequately justified theoretically?
The seminar also discusses statistical methods that are useful for answering the research question and to verify the hypotheses formulated. The empirical analyses are carried out using R, a free statistical program available for download.

Learning Outcomes
Assuming that you have read the material and participated regularly in class, the seminar will:
- sharpen your ability to produce original research in social science while developing skills in designing and conducting research studies, collecting and analysing data, drawing appropriate conclusions based on statistical results, and writing up scientific reports;
- help you choosing your MA thesis research question, collecting data and evidence, drawing conclusions and writing up your thesis;
- help you in analysing quantitative data and interpreting your results using R, a common statistical analysis programme used in the social sciences;
- develop your capacity for critically evaluating scientific evidence that is communicated in academic journals, the popular press, and other outlets such as reports from government agencies, non-profit organizations, and corporations.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students will be assessed based on their ability to formulate and implement a research question as well as on their knowledge of key quantitative skills.

Mindestanforderungen und Beurteilungsmaßstab

The final grade is made up of:
- assignments (40%),
- research outline (10%),
- final paper (40%),
- participation (10%).
Only 2 class absences are allowed.

All assignments are STRICTLY MANDATORY and must be handed in order to receive a passing grade.

Prüfungsstoff

Introduction to R, fundamentals of statistical programming
Theory & Hypotheses, Asking Research Questions
Describing data using tables and summary statistics; transforming variables
Causal inference: experiments, natural and quasi-experiments, and observational research
Describing bivariate relationships using cross-tabulations and comparisons of means and proportions
Case studies and case selection in quantitative research; Measurement; Doing a literature review
Describing data using graphs (Bar charts, histograms)
Getting Data; Gathering data: survey design; Obtaining and analyzing secondary data
Describing bivariate relationships using scatterplots
Inference: probability theory and confidence intervals. Hypothesis testing
T tests chi squared test
Bivariate regression models
interpreting coefficients +
Regression Diagnostics & Goodness of Fit
Multivariate regression analysis: logic of control variables
Categorical Variables & Interaction terms
More Complex Data: Panel & Multi-level Models, Time-series
Logistic regression

Literatur

Kellstedt, P. M. and Whitten, G. D. (2018) The Fundamentals of Political Science Research, Cambridge University Press.

Bailey, Michael A (2016 or 2020) Real Stats: Using Econometrics for Political Science and Public Policy, Oxford University Press

Other readings will be provided

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Di 08.03.2022 15:08