Quantitative Data Analysis: Macro-data in comparative research 3502-ADI-6
The purpose of this course is to enable students to get experience using publically available datasets of social data and providing ways of utilizing them for writing their M.A. thesis. The course includes presentation of the data collections, overlook of their underlying assumptions, structure and content.
Following data collections will be used during the course: Quality of Government, Comparative Political Dataset, World Bank Development Indicators, Comparative Manifesto Project.
Students will be encouraged to create their own datasets for quantitative research by finding ways for coding qualitative data. The course program includes also basic statistical method needed to analyze such data such as interaction effects and lagged variables.
Special attention will be devoted to indicators used for quantitative research in political sociology for party system research.
Type of course
Mode
Prerequisites (description)
Learning outcomes
Has in-depth knowledge of selected methods and techniques of social research, their limitations, specificity and areas of application
Is aware of the importance of a reflective and critical approach to the results of social research, analyses and research procedures
Knows how to plan and carry out complex qualitative and quantitative empirical research; is aware of the consequences of methodological choices
Can use theoretical categories and research methods in the description and analysis of social and cultural changes in modern societies, as well as their consequences
Can plan and carry out a social study using advanced quantitative and qualitative methods and techniques of social research
Can use a selected computer program for data analysis, including its advanced functions
Can prepare a presentation of a selected problem or study in Polish and in a foreign language
Can gather, find, synthesize and critically assess information about social sciences
Can argue a thesis using scientific evidence
Takes responsibility for planned and performed tasks
Assessment criteria
Preparation of one’s own dataset accompanied with a codebook or writing a report based on macro data analysis. Class attendance required. Two absences allowed without consequences. Two more need to be justified. Project assignments can be corrected at home and resubmitted for reevaluation.
Students’ total workload:
30h in class
20h compulsory readings
40h preparation of the final assignment
Practical placement
n/a
Bibliography
Basic literature includes codebooks of datasets and the following:
● Brambor, Thomas, William Roberts Clark, Matt Golder. 2006. Understanding Interaction Models: Improving Empirical Analyses. „Political Analysis” 14: 63–82.
● Jaccard, James, Robert Turrisi. 2003. Interaction Effects in Multiple Regression. Second Edition. Thousand Oaks, London, New Delhi: Sage Publications Inc, p.1-43.
● Rafałowski, Wojciech. 2018 “Values versus Interests Dynamics of Parliamentary Campaigns” Political Preferences 19.
● Markowski, Radosław. 2003. Propozycja „Manifesto Research Group”: Metoda, wyniki, problemy – komentarz”. In: Radosław Markowski - (ed.), System partyjny i zachowania wyborcze
Dekada polskich doświadczeń”. Warszawa: Instytut Studiów Politycznych PAN, Friedrich Ebert Stiftung
● Metcalf, Lee Kendall. 2000. Measuring Presidential Power. „Comparative Political Studies” 33(5): 660-685.
● Powell, Eleanor N., Joshua A. Tucker. 2013. Revisiting Electoral Volatility in PostCommunist Countries: New Data, New Results and New Approaches. „British Journal of Political Science” 44 (1): 123-147.
● Rafałowski, Wojciech. 2017. Opisywanie i wyjaśnianie systemu partyjnego. Metody pomiaru. Warszawa: Aspra-JR.
● Taagepera, Rein, Bernard Grofman. 2003. Mapping The Indices of Seats–Votes Disproportionality and Inter-Election Volatility. „Party Politics” 9(6): 659-677.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: