SOS9009 – Advanced statistical methods course
Course description
Course content
This course cover selected topics in statistical methods and research workflow related to statistical analysis. The topics covered are typically not included in statistical methods courses at the Master’s Level. In academic and applied research in sociology and allied disciplines, methods knowledge is key. The same holds for individuals with sociology degrees in business and government roles for. Statistical social science is moving forward at high speed, and this course delivers practical and theoretical knowledge that allow students to do cutting-edge analyses and implement efficient workflows.
The course will consist of a set of modules, each taught through a two-day workshop. The modules included may change (and likely will) each semester the course is taught. Students’ preferences is accommodated as far as possible in module selection.
We will use Stata and R as our main tools. This decision is made independently for each module. Language of instruction is English, unless all students have a sufficient command of Norwegian.
Learning outcome
The learning outcome of the course is mastery of a suite of methods and workflow styles that will enable the student to produce several new statistical analyses and correctly and efficiently present the results from those analyses.
Admission to the course
The course is available for PhD candidates at the Department of Sociology and Human Geography. In case there are open places, PhD candidates in sociology and geography from other universities and advanced Master’s level students may be admitted. Maximum enrollment is 20 students.
PhD students at the Department of Sociology and Human Geography register for the course in Studentweb.
Participants outside the Department of Sociology and Human Geography and Master students shall fill out this application form.?
Master students register for the course's equivalent: SOS4022 - Advanced Statistical Methods.
The application deadline is six weeks prior the course. For dates see the semester page.
Formal prerequisite knowledge
Participants must have a good working knowledge of basic statistics and linear regression analysis. Having completed SOS4020 or equivalent is sufficient preparation for the course.
Overlapping courses
- 5 credits overlap with SGO9009 – Advanced statistical methods (discontinued).
Teaching
The course consists of four modules. Each module is taught separately as a two-day workshop. Readings associated with each module will be published on the semester page. Some modules will be taught by external teachers.
For modules and readings for the next Spring semester, see the semester page.
This course has jointly taught classes with SOS4022 - Advanced Statistical Methods (master-level).
Examination
To obtain 5 ECTS credits (it is not possible to obtain less or more credits than 5):
- each module requires active class participation, readings and submission of a short assignment. Assignments due one week after the module.
- students must participate and complete in minimum three modules
- the three modules must be taken in the same semester
As the content of the course varies over semesters, it is possible to take the course several times, but it is not possible to obtain credits more than once.
Master students find detailed information about course requirements on the webpage of the master-variant of this course - SOS4022. Please go to this page for further information as requirements for master students are slightly different from those for PhD students.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.