Kristiania Univeristy of Applied Sciences
Introduction
The aim of this course is to develop a deeper understanding and applied knowledge of traditional multivariate analysis techniques in social sciences among PhD candidates. The course starts with the discussion of research questions that can be addressed through quantitative research methods. We will then present a general overview of approaches to designing quantitative studies, analysing quantitative data, and interpreting findings.
Learning Outcomes
Upon completion of the course, the candidate has achieved the following learning outcomes, defined in terms of knowledge, skills and general competence:
Knowledge
The candidate …
- has a deep insight into fundamental concepts and methods in multivariate statistics.
- has in-depth knowledge of various approaches to analysing multivariate data.
- is in the forefront of knowledge of quantitative research from a social science perspective.
- has the ability to assess how different quantitative methods can be used within social science information technology research.
Skills
The candidate …
- can transform theoretical research problems into hypotheses that can be tested using the relevant research method.
- can design and conduct a quantitative research study.
- can communicate research findings and method in a scholarly manner.
- has the ability to evaluate published quantitative research from a methodological perspective.
General competence
The candidate …
- can provide feedback on research papers that use multivariate statistics.
- can reflect upon different methodological approaches to quantitative research and critically assess published quantitative research.
- can take part in discussions on methodology, such as those implemented in the leading information technology journals in the social sciences.
Degree
PhD in Communication and Leadership
Learning activities
The course will include lectures and lab exercises. The course will consist of 24 hours divided between two modules. Assessment will involve writing a quantitative research paper. Participants may use their own dataset or data provided by the course.
Teaching dates: 12.11., 13.11., 26.11., and 27.11.2025.
Tools
TBA – (Stata/SPSS/Mplus/EQS/R)
Compulsory assignments
Non-verifiable coursework requirements: one or more assignments that must be collectively approved
Individual qualification: G/IG (approved/not approved)
Execution: individual
Verifiable (right of appeal): no
Coursework requirements are to be handed in or conducted in accordance with information given by the lecturer and carried out within the duration of the course, as well as registered as approved/not approved at least two weeks before the exam/exam period.
Approved coursework requirements grant students permission to take exams. Unapproved coursework requirements result in the student’s withdrawal from the exam.
Examination
Exam: Individual written home examination
Duration: Semester
Grading scale: The Norwegian grading system uses the graded scale pass or fail
Weighting: Passing of the overall assessment
Support materials: All support materials are allowed
If graded fail the candidate can resubmit the written home exam within 2 weeks from the grade is announced. The number of attempts for the exam is stated in the regulations.
Application deadline: 12.10.205