Quantitative Methods

Postgraduate course

Course description

Objectives and Content

The course aims to enable students to critically engage with existing quantitative analyses and to conduct their own quantitative studies. An essential skill in working with quantitative methods is understanding what conclusions can be drawn based on the data and the methods used. By focusing on linear regression and generalized linear models, students will develop their skills in identifying appropriate research designs and in conducting sound statistical modeling given different data structures. Other analytical techniques, such as multilevel analysis and experimental methods, are also emphasized.

When students begin work on their master’s thesis, the goal is for them to be able to make independent and well-justified methodological choices.

Learning Outcomes

Upon completion of the course, the student should have achieved the following learning outcomes, defined in terms of knowledge, skills, and general competence:

Knowledge

The student...

  • has knowledge of various data structures and understand the problems that arise when unsuitable models are used to analyze data
  • has knowledge of the logic of experimental methods and of the differences between various experimental designs

Skills

The student...

  • can assess strengths and weaknesses of selected strategies for identifying (causal) relationships in quantitative studies
  • can handle data and carry out regression analysis in the chosen statistical software in accordance with good statistical practice
  • can test, diagnose and adjust basic statistical models to ensure reliable results
  • can present and visualise data and results from statistical models in a clear and academically appropriate manner
  • can use relevant statistical software independently and reflectively in analytical and written work

General Competence

The student...

  • can identify and discuss strengths and weaknesses of different methodological approaches
  • can conduct responsible data processing and document the workflow in accordance with academic and professional standards
  • can critically evaluate the scope and limitations of one’s own and others’ research findings

ECTS Credits

10 ECTS

Level of Study

Master

Semester of Instruction

Spring
Required Previous Knowledge
None
Recommended Previous Knowledge

AORG101, AORG104, AORG103 / AORG105 / AORG107 / AORG109, AORG209 / AORG210

or 

GOV101, GOV104, GOV103 / GOV107 / GOV109

Credit Reduction due to Course Overlap
  • AORG321A (10 ECTS)
  • AORG321B (10 ECTS)
  • AORG319 (10 ECTS)
  • AORG321 (10 ECTS)
Access to the Course

The course is open for students who have been accepted to Master programmes at the Department of Government.

Exchange students at master level may be accepted upon application. Applications may be rejected due to capacity.

Teaching and learning methods
The format of teaching is primarily class lectures (6-7). In addition, 3-4 seminars will be given where students are required to participate in practical exercises in using statistical software to prepare and analyze datasets.
Compulsory Assignments and Attendance

Participation in practical exercises organized through seminars is compulsory. A minimum of 75% attendance at the seminar is required.

The assignments in the seminars must be completed in order to take the exam. Approved compulsory assignments are valid in the current and following two semesters.

Forms of Assessment

A five-hour school exam.

The exam will be given in the language in which the course is taught.  The exam answer can be submitted in English, Norwegian, Swedish or Danish.

Grading Scale
Graded A-F
Assessment Semester

Assessment in teaching semester.

A retake exam is arranged for students with valid absence according to UiBs study regulations § 5-5.If there is a retake exam for students valid absence, students with the following results/absences can register for the exam:

  • Interruption during the exam
  • Fail/failed

Students can register themselves in Studentweb after 1. August

Reading List
The reading list will be ready before 1 July for the autumn semester and 1 December for the spring semester. 
Course Evaluation
All courses are evaluated according to UiB's system for quality assurance of education.
Examination Support Material
Dictionary preapproved by the Faculty
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.  
Course Administrator
Department of Government at the Faculty of Social Sciences has the administrative responsibility for the course and the study programme.