FORK 1005 Preparatory course in Mathematics for Multivariate Statistics, MSc


FORK 1005 Preparatory course in Mathematics for Multivariate Statistics, MSc

Responsible for the course
Steffen Grønneberg

Department of Economics

According to study plan

ECTS Credits

Language of instruction

We review central mathematical concepts that are especially relevant for multivariate statistics.

At the start of fall-semesters, the course will be given for students in the following programs :

- Msc in Leadership and Organizational Psychology
- Msc in Strategic Marketing Management

At the start of spring-semesters, the course will be given for students taking a MSc in Business with the following specializations:

- Business Law, Tax and Accounting
- International Business
- Logistics - Supply Chain and Network
- Marketing
- Strategy

This course is not relevant for students doing MSc in Finance or MSc in Business, major Finance or Economics.

Learning outcome
To provide the basic mathematical tools for multivariate statistics courses to students who need to refresh their mathematical skills.


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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Compulsory reading

Reading material will be distributed on It`s learning before the course starts.

Recommended reading

Course outline
The course reviews the mathematical theory surrounding applied statistics at the level of multiple linear regression. This includes calculation rules with the summation notation, standardization of random variables and its use for Normally distributed random variables, and related mathematical issues.

Computer-based tools
Not applicable

Learning process and workload
There will be 10 teaching hours in the course.


Form of assessment Weight Group size
Not applicable

Examination code(s)
Not applicable

Examination support materials

Re-sit examination
Not applicable

Additional information
Honour code. Academic honesty and trust are important to all of us as individuals, and are values that are integral to BI's honour code system. Students are responsible for familiarising themselves with the honour code system, to which the faculty is deeply committed. Any violation of the honour code will be dealt with in accordance with BI’s procedures for academic misconduct. Issues of academic integrity are taken seriously by everyone associated with the programmes at BI and are at the heart of the honour code. If you have any questions about your responsibilities under the honour code, please ask. The learning platform itslearning is used in the teaching of all courses at BI. All students are expected to make use of itslearning.