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210112 UE M2: Research Methods for Political Science (2022S)
(engl.)
Continuous assessment of course work
Labels
Eine Anmeldung über u:space innerhalb der Anmeldephase ist erforderlich! Eine nachträgliche Anmeldung ist NICHT möglich.
Studierende, die der ersten Einheit unentschuldigt fern bleiben, verlieren ihren Platz in der Lehrveranstaltung.Achten Sie auf die Einhaltung der Standards guter wissenschaftlicher Praxis und die korrekte Anwendung der Techniken wissenschaftlichen Arbeitens und Schreibens.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis).
Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Studierende, die der ersten Einheit unentschuldigt fern bleiben, verlieren ihren Platz in der Lehrveranstaltung.Achten Sie auf die Einhaltung der Standards guter wissenschaftlicher Praxis und die korrekte Anwendung der Techniken wissenschaftlichen Arbeitens und Schreibens.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis).
Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
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).
- Registration is open from Fr 11.02.2022 08:00 to Mo 21.02.2022 08:00
- Registration is open from We 23.02.2022 08:00 to Mo 28.02.2022 08:00
- Deregistration possible until Fr 18.03.2022 23:59
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 10.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 17.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 24.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 31.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 07.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 28.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 05.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 12.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 19.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 02.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 09.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 23.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
- Thursday 30.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Information
Aims, contents and method of the course
Assessment and permitted materials
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.
Minimum requirements and assessment criteria
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.
- 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.
Examination topics
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
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
Reading list
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 PressOther readings will be provided
Association in the course directory
Last modified: Tu 08.03.2022 15:08
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.