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Postgraduate course

Quantitative Methods and Research Planninged Statistical Analysis

  • ECTS credits10
  • Teaching semester
  • Course codeGLODE304
  • Number of semesters
  • LanguageEnglish
  • Resources

Main content

ECTS Credits

15 ECTS

Level of Study

Master's

Full-time/Part-time

Full time

Teaching semester

Spring

Objectives and Content

This is a specialization course in quantitative methods, research planning and applied statistical analysis. It offers an introduction to theory of knowledge and research methodologies, but gives emphasis to planning quantitative research and methods of statistical analysis of quantitative data within the social and health sciences. Students learn the fundamentals of writing a quantitative master¿s thesis proposal as well as the fundamental operations using SPSS.

Learning Outcomes

On completion of this course the students should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge:

The student will have in-depth knowledge of:

  • Different knowledge paradigms and explanatory models, and their implications for choice of methodological strategy
  • Key concepts and theories within quantitative and qualitative methodologies, mixed methods.
  • Ethical principles in research and their application in quantitative and qualitative research
  • The requirements for the master's thesis proposal
  • The appropriate use of a range of statistical methods/techniques
  • The interpretation of statistical analysis

Skills:

The student has the ability to:

  • Pose study questions that can be addressed using statistical methods, e.g., hypothesis testing
  • Model data using alternative approaches and decide on final approaches to an analysis
  • Annotate and interpret output from statistical analyses
  • Format tables and graphs that present statistical analyses
  • Design a research project and write a project plan

General competencies:

By the end of the course the student:

  • Can critically, analytically and systematically evaluate research literature (in both qualitative and quantitative methods)
  • Can think critically, reflectively and creatively about statistical analysis
  • Has methodological competencies for statistics-related skills problem-solving
  • Can choose appropriate statistical analyses given the nature of the study data

Required Previous Knowledge

Completion of the first semester of study in the master's programme in Global Development Theory and Practice, Child Protection and Welfare or Health Promotion and Psychology.

Access to the Course

Open to all students registered in the Master's Programmes at the Department of Health Promotion and Development.

Teaching and learning methods

The teaching methods will consist of lectures and seminars.

Teaching Methods and Extent of Organized Teaching

The teaching methods will consist of lectures and computer laboratory sessions.

Compulsory Assignments and Attendance

  • 80% compulsory attendance in seminars
  • Submission of analyses done in SPSS, plus interpretation of results.
  • Development of project plan for master thesis
  • Presentation of own research project for fellow students

All activities must be completed and approved before the student's final exam kan be evaluated.

Forms of Assessment

Home exam, 5 days

Grading Scale

A-F

Assessment Semester

Spring 

Reading List

Will be made available on 1st December.

Course Evaluation

The course will be evaluated in accordance with the Faculty of Psychology's routines for participatory evaluation and the University of Bergen's Quality Assurance System.

Programme Committee

Department of Health Promotion and Development, Faculty of Psychology

Course Coordinator

Department of Health Promotion and Development, Faculty of Psychology.

Course Administrator

Department of Health Promotion and Development, Faculty of Psychology.

Exam information

  • Type of assessment: Home exam

    Assignment handed out
    22.08.2022, 09:00
    Submission deadline
    26.08.2022, 15:00
    Withdrawal deadline
    08.08.2022
    Examination result announcement
    05.09.2022
    Examination system
    Inspera
    Digital exam