STV4030C – Survey Data Analysis and Design in Political Science
Course content
This course introduces students to the analysis of existing survey data, as well as to the science and practice of designing surveys. The first half of the course covers key aspects of survey design, including definition of a population, sampling of respondents, design of survey questions, response alternatives, the overall survey structure, survey-embedded experiments, and research ethics. The course’s second half covers the use and analysis of existing comparative, national, and local surveys to answer research questions. Students will become familiar with the most prominent existing surveys in political science, ranging from population-based surveys such as the European Social Survey (ESS) or expert surveys such as Varieties of Democracy (V-DEM), and be set up to use these rich data sources in their master theses.
There are several advantages for students using existing surveys. For instance, question batteries included in major survey data collections are often validated scales from established literatures, their samples are typically more representative than primary surveys, and using existing datasets is less costly than collecting primary survey data. The course will provide an overview of existing survey datasets and how to access, manage, and effectively analyze these datasets for answering research questions.
The course is practically oriented in that students learn to analyze existing survey data and design their own surveys with concrete tasks throughout the course that will amount to a portfolio. These tasks will be assisted in the course’s seminars. The course also covers analytical approaches which are specifically relevant for survey research, including power analysis, weighting of survey responses, and factor analysis. At the same time, the lectures emphasize learning and applying general insights from the large research field on how design decisions affect empirical results.
The course is of immediate relevance for students planning to use primary or secondary survey data in their master thesis. The course should be generally useful for most students given the increasing use of surveys and questionnaires in settings where political scientists make a living (the examples include public administration, journalism, non-governmental organizations, political parties, and public opinion).
Learning outcome
After having completed the course, the students have acquired the following knowledge, skills and general competencies:
Knowledge
Students learn
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about existing survey datasets relevant for answering research questions in political science
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the "state-of-the-art" in the research literature on survey design and survey experiments
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numerous political science examples and applications present in the literature
Skills
Students learn
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to identify, access, manage and analyze existing survey data in R
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how to design their own surveys
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how to design survey experiments in order to answer political science research problems
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to identify and improve research design choices relevant for various research problems
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to communicate academic knowledge in writing and orally
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General competencies
Students improve
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their skills in managing and analyzing quantitative data
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their communications skills, in particularly in issues related to survey design
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their skills in giving constructive feedback on research design choices
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their academic writing skills, particularly in issues related to survey design.
Admission to the course
Students must be enrolled in the master programmes in Political science.
Recommended previous knowledge
STV4021 – 澳门皇冠体育,皇冠足球比分sdesign i statsvitenskap and STV4022 – Anvendt statistikk for statsvitenskap, or PECOS4025 – Analytic perspectives on peace and conflict and PECOS4022 – Applied Statistics for Peace and Conflict Studies?or?equivalent.
Teaching
Lectures and seminars.
Seminars will be used to work on four tasks. The first will ask students to design their own survey to answer a research question; the second will prompt them to research existing survey batteries. The final two assignments will center on analysis of existing survey data, with one asking students to download and perform initial data management of the dataset, as well as some descriptive statistics. The final task will be to perform some type of regression analysis using latent concepts.
Compulsory activities
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Attend at least three of five seminars.
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Students hand in four tasks, consisting of max 1500 words. Each will be due two working days after the corresponding seminar in which students are given time and assistance to work on the tasks. Students are then given feedback on their work. At the end of the course, tasks that take this feedback into account will make up the portfolio exam.
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Absence from compulsory activities: For many courses, UiO requires participation in the form of compulsory activities. These must be approved before you can sit for the examination. If you are ill or have another valid reason for being absent from compulsory activities, your absence may be approved or the compulsory activity may be postponed. Report absence from or the need for a postponed deadline on a compulsory activity: Absence from compulsory activities – University of Oslo (uio.no).
Examination
Portfolio exam. The portfolio is made up of the four tasks produced throughout the course: 1) design of primary survey, 2) researching existing surveys 3) analysis part 1 – data download and management, including handling of missing data, descriptives 4) analysis part 2 – regression analysis using latent concepts, including weighting, factor analysis and regression. The knowledge and skills to perform each task is given in the lectures and assisted in the seminars. Final tasks included in the portfolio should incorporate feedback given by seminar leaders/course convenors. Successful completion of this portfolio exam means that students are capable and ready to analyze survey data in their own master theses.
Language of examination
The examination text is given in English, and you submit your response in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about?the grading system.
Resit an examination
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