Quantitative Methods

University of South-Eastern Norway

Required prerequisite knowledge

The course builds on knowledge that can be assumed known from studies at a Master’s level.

The recommended prerequisites are essential skills and knowledge in methods such as common

descriptive analysis of the distributions, central tendency and variation estimation, bivariate

regression and correlation. Also, candidates are expected to be familiar with fundamental functions

in the SPSS software.

Learning outcome

Knowledge

The candidate

  • can handle complex academic issues regarding the relation between epistemological and

ontological assumptions, paradigms, research designs and methodology with particular

emphasis on quantitative data

  • can be a critical participant in scientific discussions about requirements for precision,

reliability, validity and credibility/trustworthiness of quantitative research approaches

  • can generate, process and analyze data of high international standard and present findings in

a way that reflects the standards of international, peer-reviewed publications

  • can, in accordance with international standards, critically review and synthesize research

findings that build upon different quantitative methodological approaches

  • is familiar with several distinct approaches to quantitative research and how they relate to

different theoretical stances

  • has in-depth knowledge about ethical questions concerning the interaction between

researcher and research participants, and the use and representation of research dataSkills

The candidate

  • can critically evaluate the appropriateness of different quantitative research designs as well

as research methodologies and methods of data generation and analysis

  • can critically evaluate the research-methodological quality of their own and others’ work, in

terms of reliability, validity and potential for generalization

  • can evaluate and contribute to the development of quantitative research designs and

research methods, and critically evaluate their potential for generating knowledge

  • can develop and assess instruments to be used in data collection (e.g. survey data and factor

analysis)

  • can evaluate practical aspects related to the use of different methods and their combination

in the context of completing a doctoral dissertationCompetencies

The candidate

  • can place and critically evaluate quantitative research and communicate this to other

academics in and beyond their own disciplines

  • can relate, in ethically justifiable ways, to quantitative research methodologies, for gathering

and analyzing data as well as to the storage of research data and results

  • can identify new relevant quantitative methodological issues and carry out his/her research

with scholarly integrity

Learning activities

This course unit consists of topic-oriented lectures and exercise sessions including the use of

software such as SPSS, as well as written assessments. The candidates are responsible for completing

the given assessments in the unit and will have to exercise self-allocation of activities within the

framework of the unit. Active contributions from the candidates in form of discussions with peers

and course instructors are expected. Also, students will be asked to present a critical reading of one

empirical study from the reading list of the course. This presentation will be delivered as a videoreflection

between day 2 and day 3, and will be available for all course participants.

Compulsory Activity

The participants must deliver a short abstract of 300–500 words in which they describe and reflect on

the choice of method in their own dissertation work. This is read and commented on by fellow

students in groups. This and other (obligatory) activities will be further specified in the course

syllabus.

Minimum 80% attendance. 

Forms of assessment

Home exam.

Assessment is based on a written, individual course paper.

Maximum 3,000 words; the topic should relate to the candidates’ own research. The paper should

use literature from the course.

Grades are awarded on a pass/fail scale. The minimal requirement for pass is that the paper would

receive at least the grade B (very good) on a scale from A (excellent) to F (fail).

The paper will be examined by an internal and an external examiner.

Literature (reading list)

The reading list is not published yet.

Application deadline: 1.11.2025