PLU8012 - Applied Quantitative Research Methods of Analysis


Examination arrangement

Examination arrangement: Assignment
Grade: Passed / Not Passed

Evaluation Weighting Duration Grade deviation Examination aids
Assignment 100/100

Course content

This is an introductory course in quantitative methodology. The course prepares for design, data collection, and analysis of quantitative data. It combines thory and practical analysis of data on IBM SPSS.Research ethics are dealt with in different parts of the course. These themes are emphasised; Information to and the active consent from respondents, ethical aspects of research questions, ethical considerations in the use of sources, transparency in all aspects of research and of the reporting results and conclusions

Learning outcome

The goal is to introduce students to quantitative methods as part of PhD education.


  • The candidate has knowledge of fundamental statistical concepts and analyses in quantitative methodology including factor- and regression analysis.


  • The candidate can prepare survey inquiries, prepare analyses and do data analysis in IBM SPSS using common analytical techniques.

General competence:

  • Candidates are capable to do research projects, which involve using quantitative methods, write scientifically about the project and the results and be able to use their skills to tutor candidates who use quantitative methods.

Learning methods and activities

The course is block-scheduled with lectures, discussions and work with statistical data on SPSS. Participants may use their own dataset or data provided by the course. Lectures are based on practical research combined with literature. Teaching combines theoretical understanding, tutorial and practical analytic skills.Teaching uses little practical mathematics in order to gain knowledge. If the course have English students, the teaching will be in English. Assignments can be handed in in Norwegian or English.

Compulsory assignments

  • Obligatory attendance 80%

Further on evaluation

Individual paper. Assessments are based on submission of a paper with 10-12 pages based on analysis of an empirical example from own or borrowed dataset.

Specific conditions

Limited admission to classes. For more information:

Compulsory activities from previous semester may be approved by the department.

Required previous knowledge

Master's degree or equivalent university degree, where Ph.D. students will be given first preference for admission. Admission restrictions*: The course is limited to a of maximum 25 students, where 6 spots are reserved for applicants from other institutions affiliated with NorTED ( If there are less than 5 applicants, the Department of Teacher Education reserves the right to cancel the course. * Applicants will be ranked based on the following criteria and deadline for applications can be found here:

Course materials

The course uses the following literature (in Norwegian)Christophersen, K. A. (2012). Databehandling og statistisk analyse med SPSS. Oslo: Akademika. Ringdal, K. (2013). Enhet og mangfold. Bergen: Fagbokforlaget. Ulleberg, P., & Nordvik, H. (2001). Innføring i faktorteori og faktoranalyse. Trondheim: Tapir. Utdelte artikler - kompenidum.Equivalent English literature is possible. The participants need to have PC/MAC with latest version of IBM SPSS.

More on the course

Version: 1
Credits:  5.0 SP
Study level: Doctoral degree level


Term no.: 1
Teaching semester:  SPRING 2023

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Teacher Education
  • School Development
Contact information
Course coordinator:

Department with academic responsibility
Department of Teacher Education


Examination arrangement: Assignment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Assignment 100/100 INSPERA
Room Building Number of candidates
Spring ORD Assignment 100/100 INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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