Quantitative Methods

This course is a mandatory course in the master's programme in Contemporary Issues in Risk and Crisis Management (CRCM).

The course can also be taken as a single course and is equivalent to the course SVF-3004 "Kvantitativ metode".

The course focuses on the research process in quantitative studies. The emphasis is on the implementation of quantitative research designs. Data collection and dataset construction will be central. Dimensions, levels, and temporal aspects of data will be discussed. The main focus is on various forms of regression analysis, including both OLS and MLE models, including logistic regression and survival models.

Completed bachelor's degree.

Application code: 9371 - single course master's level.

After completing the course, students should have the following learning outcomes:

Knowledge

The student has:

• Good knowledge of quantitative research
• Good knowledge of dataset construction and data systematization
• Knowledge of how to apply different statistical analyses
• Understanding of a quantitative research process from planning to report/thesis.

Skills

The student can:

• Conduct all parts of a quantitative study independently
• Use statistics in a research process and in reports/theses
• Analyse different types of quantitative data.

Competence

The student can:

• Conduct a small social science study with a quantitative perspective, such as their own master's thesis.

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

• SVF-3004 Quantitative research methods 10 ects
• PED-3050 Quantitative methods 10 ects
• STA-3301 Applied statistical methods and data analysis 10 ects
• SVF-3212 Research Design and Method in Societal Security 5 ects

The teaching consists of pre-recorded online lectures (12-15 lectures each 20 min) and pre-recorded online seminars with practical exercises (6-8 seminars each 20 min). All course material, including lectures, seminars, and tasks, are digitalized.

The course involves practical work with data collection from various sources, dataset construction, and statistical analysis, as well as searching for relevant method literature.

Language of instruction and examination

Schedule

This course is open to incoming exchange students.

Study level: Master’s

Admission prerequisites:
This course has admission prerequisites, which are listed under the Admission requirements section. Please review this information carefully before adding the course to your Learning Agreement.

For details on how to apply for exchange, course selection guidelines, or to contact the Incoming Admissions Team, please visit: Admissions for Student Exchange.

Re-sit examination