LMSM130 Quantitative Methods

    • Course code
      LMSM130
    • Number of credits
      7,5
    • Teaching semester
      2026 Spring
    • Language of instruction
      English
    • Campus
      Lillehammer
    • Required prerequisite knowledge

      None

Course content

This course provides students with a solid foundation in quantitative methods. The topics covered are:

  • The philosophy of quantitative methods
  • Research strategy and design
  • Data collection, analyses, and interpretation. Reliability and validity
  • Visualization
  • Multiple linear regression and regression assumptions
  • Logistic regression
  • Instrumental variables regression
  • Models for panel data
  • Exploratory and confirmatory factor analysis
  • Academic writing
  • Ethical and legal issues in quantitative research

Learning Outcome

Knowledge

Upon completion of the course, the candidate shall:

  • Have advanced knowledge about research design, data collection, analyses, and interpretation of research results based on quantitative methods (k1)
  • Have in-depth knowledge about multiple linear regression and its assumptions and interpretation (k2)
  • Have detailed knowledge about logistic regression, instrument variables regression and panel data models (k3)
  • Be familiar with exploratory and confirmatory factor analysis (k4)
  • Know about ethical and legal issues related to data collection and privacy in the use of quantitative analyses (k5)
Skills

Upon completion of the course, the candidate shall be able to:

  • Design questionnaires and collect data using appropriate tools and techniques (f1)
  • Apply statistical software to run regression analysis (f2)
  • Examine the underlying assumptions of OLS estimation using statistical tests and visualizations (f3)
  • Distinguish between the probabilistic and the causal interpretations of regression and estimate both predictive and causal effects (f4)
  • Compare various model specifications and make qualified decisions on how appropriate they are in applications (f5)
  • Demonstrate professional reporting and writing skills by preparing a short academic paper using the insights from the topics covered in the course (f6)  
General competence

Upon completion of the course, the candidate shall be able to:

  • Complete a research project using the quantitative methods covered in the course (g1)
  • Communicate key results from own and others’ research and debate the findings and the uncertainty of the results with peers (g2)
Teaching and working methods

The following teaching methods are used:

  • Lectures
  • Problem solving sessions, individually and in groups
  • Tutorial videos
  • Case studies
  • Quizzes

The teaching activities at the meetings are aligned with the expectation that students have prepared for the relevant meeting by reading and other self-learning activities, including written work (see coursework requirements). Expected total work effort in the course is 187.5-225 hours (according to ECTS standard).

Required coursework
  • Mandatory homework assignments must be handed in before each teaching module (a total of 4). The assignments are based on cases (data sets will be distributed) and must be solved in groups of up to three students. Three out of four homework assignments must be passed to be allowed to take the exam. The students themselves are responsible for forming groups.
  • Attendance on at least 50% of the courses lectured teaching.
Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Written examination with invigilation
ECTS - A-F
Individual
4 Hour(s)
  • No support materials
60 %
Written assignment
ECTS - A-F
Group (2 - 3)
Semester(s)
  • All
40 %
Form of assessment
  • 4-hour individual school exam under attendance (counts 60% of the grade).
  • Homework assignment with a given problem, in groups of up to three students (counts 40% of the grade). The semester assignment requires the use of statistical software.

Both exams must be passed for the student to pass the course.

Graded A-F, where E is minimum for passing the exam.

At the group exam, all group members are responsible for all content in the answer.

Professional overlap
NameCreditsDateComment
3MSM130 Kvantitativ metode
7,5
KMSM130 Kvantitativ metode
7,5
INN3041 Kvantitativ metode
7,5
Course name in Norwegian Bokmål: 
Quantitative Methods
Faculty
Inland School of Business and Social Sciences
Department
Department of Business Administration
Area of study
Økonomisk-administrativ utdanning
Programme of study
Master of Science in Business Administration - majoring in Business Analytics
Course level
Second degree level (500-HN)