MET 1190 Statistics

Norwegian version

MET 1190 Statistics

Responsible for the course
Christian Brinch

Department of Economics

According to study plan

ECTS Credits

Language of instruction

The use of abstract mathematical and statistical models to describe and analyze a complex reality has in many areas proved useful. In this course students are introduced to useful and well established methods that are applicable in practice.

Learning outcome
After completing the learning process described in this course description, students will:

Aquried Knowledge
Based on a through understanding of concepts and notions in probability and statistics, the students will understand that statistical techniques and methods are based on assumptions and requirements.

Aquired Skills

  • be able to handle and analyze quantitative uncertainty and probability
  • be able to model using discrete and continuous stochastic variables, and be capable in handling, analyzing and presenting data related to these with and without using computerized tools
  • be able to handle the sample of a population and be capable in methods for statistical inference
  • be able to select correct model and test in different situations and be able to conclude from these
  • be able to compute with probabilities
  • be able to estimate a simple regression model

  • On completion of the course the students will have developed a critical attitude towards results and the validity of statistical analysis.

Basic skills in mathematics and statistics equivalent to admission requirements for the program.

Compulsory reading
Løvås, Gunnar G. 2013. Statistikk for universiteter og høyskoler. 3. utg. Universitetsforlaget. kap 1-7

Recommended reading

Course outline
  1. Descriptive statistics
  2. Stochastic experiments and stochastic variables
  3. Computation with probabilities, elementary set theory
  4. Discrete probability distributions
  5. Continuous probability distributions
  6. Inference for parameters in discrete probability distributions
  7. Inference for parameters in continuous probability distributions
  8. Estimation
  9. Hypothesis testing
  10. Simple linear regression
  11. Inference in simple linear regression model
  12. Selection of model and methods

Computer-based tools

Learning process and workload
To each lecture there will be exercises and reading assignments. The student must gain knowledge from the material presented in the reading assignments and work through the exercises. Some of the exercises must be solved using Excel. The exam will require that the student has solved the exercises during the semester. Feedback will be given by sample solutions and presentations.

Workload for the student:
Use of hours
Work with exercises (and computer-base tools)
Reading assignments
Preparation for final exam
Recommended use of time

    A five hour individual exam, concludes the course.
    Examination code(s)
    MET 11901 - Written exam, counts 100% towards the final grade in MET 1190 Statistics, 7,5 credits.

    Examination support materials
    All support materials + BI approved exam calculator. Examination support materials at written examinations are explained under examination information in the student portal @bi. Please note use of calculator and dictionary in the section on support materials (

    Re-sit examination
    Re-sit examination is offered every term.

    Additional information