GRA 6035 Mathematics

GRA 6035 Mathematics

Course code: 
GRA 6035
Course coordinator: 
Eivind Eriksen
Course name in Norwegian: 
Product category: 
MSc - Core course
2024 Autumn
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

The language of mathematics is extensively used to analyse problems in economics and finance, and mathematical models, theories, and methods are extensively used to solve problems. The mathematical requirements of a graduate student go beyond the material usually taught in undergraduate courses, and this course will teach the beginning graduate student more advanced mathematical models, theories, and methods. In particular, it will introduce the students to coding using Excel. The course is taught in the first semester of the master programme. Topics include linear algebra and matrix methods, optimisation in several real variables, and differential and difference equations.

Learning outcomes - Knowledge

After completing the course, the student will have advanced knowledge of mathematical concepts, models, theories, and methods. The student will have an advanced understanding of linear algebra and matrix methods, optimisation in several real variables, and differential and difference equations, and specialized understanding of how these mathematical models and methods can be used in economics and finance.  

Learning outcomes - Skills

After completing the course, the student will be able to analyse quantitative problems using the mathematical language, and be able to use mathematical models and methods to solve these problems. The student will be able to assess solution strategies, be able to carry out necessary computations correctly and precisely. The student will be able to give mathematical arguments for his conclusions, and be able to formulate written answers that explain the methods used and interpret the solutions obtained. The students will be able to see connections between mathematics and other subjects, especially economics and finance. 

General Competence

After completing the course, the student will be able to reflect upon central assumptions for the models and theories used, and critically assess if they are met in applications. The student will be capable of critical thinking. The student will be able to reflect upon the results obtained, and critically assess if they are reasonable.

Course content
  • Linear algebra and matrix methods
  • Optimisation in several real variables
  • Differential and difference equations
Teaching and learning activities

The course is taught over one semester, and consists of lectures (36 hours) and plenary problem solving sessions (12 hours).   

For each lecture, there will be a work program consisting of exercises and reading assignments. The student must learn the material presented in the reading assignments, and work through the exercises. Some of the exercises will be reviewed in lectures and plenary problem solving sessions. It is assumed that the student has worked with the exercises in order to take full advantage of the review. By allocating some time in class to short assignment related to new topics, students will be activated and learning objectives achieved.

Wolfram Alpha is used in lectures and problem solving sessions to illustrate taught material. Excel will be used to model, solve and visualize linear differential and difference equations. 

Software tools
Software defined under the section "Teaching and learning activities".
Additional information

The exam for this course has been changed starting academic year 2023/2024. The course now has one exam code instead of two. It is not possible to retake the old version of the exam. Please note new exam code in the Exam section of the course description. 

It is the student’s own responsibility to obtain any information provided in class.


All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.


Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Exam category: 
School Exam
Form of assessment: 
Written School Exam - pen and paper
Exam/hand-in semester: 
First Semester
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
5 Hour(s)
Final written examination under supervision.
Retake examination is offered in January (not in May/June) in the spring semester.
Exam code: 
GRA 60354
Grading scale: 
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
36 Hour(s)
Feedback activities and counselling
12 Hour(s)
Plenary session
Group work / Assignments
16 Hour(s)
Exercise sessions
5 Hour(s)
Final exam
Student's own work with learning resources
91 Hour(s)
Read theory and prepare for lectures, own work with problems
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.