ELE 3719 Mathematics elective

ELE 3719 Mathematics elective

Course code: 
ELE 3719
Course coordinator: 
Runar Ile
Course name in Norwegian: 
Matematikk valgfag
Product category: 
Bachelor - Electives
2021 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

This course gives an introduction to selected topics in mathematics and probability theory.

Please note!
Due to the Corona situation, BI Norwegian Business School has decided that the exam in this course will be changed in the spring of 2021. The course this spring will be evaluated with a home exam which counts 100%. This will be assessed as pass / fail. No one will get a letter grade. 

All students who have registered for the exam in this course in spring 2020 will be registered for this new course and exam code. This also applies to re-sit students.

The change means that the course gets a new course and exam code. Follow the link to the course description ELE 0719 Mathematics electives which will apply in the spring of 2021.

Learning outcomes - Knowledge

Upon completing this course, the student should have acquired mathematical knowledge in selected topics that are important for finance, economics and statistics. The student should:

  • Know important concepts in linear algebra and vector calculus, such as matrices, vectors, determinants and quadratic forms, and know how to use these in optimization and multivariate statistics.
  • Understand probability models from a mathematical point of view.
  • Know the concept differential equation, and know how differential equations can be used for modelling.
  • Understand foundations of calculus of variations and optimal control theory, and know how this theory can be used in economics.
Learning outcomes - Skills

Upon completing this course, the student should have acquired skills including:

  • Mastery of calculations with matrices, vectors and determinants, find eigenvalues and eigenvectors, and ability to use this in applications.
  • Ability to compute with probabilities and probability models in one or several variables, and to use this in applications.
  • Ability to solve selected types of differential equations, with and without initial conditions.
  • Ability to solve selected optimization problems.
General Competence

Upon completing this course, the student should have strengthened his/her analytical thinking, and have realized the value of precise and systematic work.

Course content
  • Linear algebra and vector calculus
  • Probability theory
  • Differential equations
  • Optimal control theory
Teaching and learning activities

The course has 45 hours of lectures. There will be work programmes with problems that the student should solve. Some of the problems will subsequently be solved in class.  

Some time in class will be set aside for the students to work on basic problems in topics recently covered in lectures. This will activate the students and increase the learning outcome through the presentation of solutions to the problems.

Software tools
No specified computer-based tools are required.
Additional information

For electives re-sit is normally offered at the next scheduled course. If an elective is discontinued or is not initiated in the semester it is offered, re-sit will be offered in the electives ordinary semester.


Higher Education Entrance Qualification


Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Required prerequisite knowledge

The course builds on MET 1180 Mathematics, or MET 2910 Mathematics.

Exam category: 
Form of assessment: 
Written submission
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
5 Hour(s)
Exam code: 
Grading scale: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
45 Hour(s)
Group work / Assignments
100 Hour(s)
Student's own work with learning resources
50 Hour(s)
5 Hour(s)
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.