STV4025 – Quantitative political science
Schedule, syllabus and examination date
The aim of the course equip students with a set of methodological tools suitable for addressing a wide range of questions common in quantitatively oriented political science. The focus is on methods for analysing data with categorical or limited dependent variable, with and without a hierarchical structure, and the practical implementation of these methods in R, a high-quality and free statistical programming language. More specifically, we will cover models for binary, ordered and multi-category choice and count models with a single dependent variable. We will then discuss issues that arise if observations are repeated for the same units over time or if units are clustered into groups with shared characteristics. Finally, we discuss models for analysing event history data, as such models can be used to analyse the duration of conflicts, legislative careers, government survival, and numerous other phenomena in political science.
- Awareness of a wide range of statistical models common in quantitative political science
- Awareness of standards for presentation of quantitative evidence in political science
- Awareness of the role of data-sharing and replication-standards for cumulative political science
- Ability to conduct independent statistical analysis
- Ability to produce scientific reports with publication-quality table and figures
- Ability to replicate and evaluate findings reported in major political science journals
- Ability to evaluate the methodological soundness of arguments based on quantitative evidence
- Ability to present quantitative findings in a written format
Students admitted to a PhD program may also be qualified for the course. Please contact the Department of Political Science.
Students admitted to other Master programmes may be qualified to apply for the course if they fulfill the requirements. Please see the webpage on Admission to single master's courses.
Formal prerequisite knowledge
STV4020 must be passed.
10 lectures will be given. The lectures are held intensively for a period of 5 weeks, with the final assignment in the sixth week.
This course will be taught at the University of Oslo, Blindern campus. Other locations in Oslo may be used. Fronter will normally be used.
The course is part of the regular course offerings at the Faculty of Social Science. Teaching is mainly held during the daytime. Detailed course-information is found on the Webpage for the current semester.
Students will be evaluated on the basis of the weekly assignments. There will not be a final school exam. All assignments must be handed in on time in order to pass the course. Each assignment will be based on a published article and a dataset. The task will be to replicate the study and extend it by using the techniques demonstrated in the lectures. The students need to submit a fully functional script and a textfile of 500–1000 words which describes the purpose of the study, the method(s) and the results. The deadline for the assignments will be before the first lecture of the following week.
Language of examination
It is possible to submit your response in Norwegian, Swedish, Danish or English.
Course grades are awarded on a descending scale using alphabetic grades from A to E for passes and F for fail.
Examination results are available in StudentWeb within three weeks after the date of the final assignment, if no other information is given on the Webpage for the current semester.
Explanations and appeals
Resit an examination
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.
This course is evaluated half way through every semester and every four year the course undergoes a thorough evaluation.
An external auditor regularly evaluates the academic quality of the course and he/she makes a written report every year.