This is the study programme for 2020/2021.

How can business enterprises make smart and well-informed decisions using the insights from the data? In this course, we will go through some of the most fundamental methods of multivariate data analysis to learn how to turn "data" into "information." Using various types of data and R software, we uncover the hidden patterns and narratives behind numbers and texts that can inform the decision-makers in this data-driven world.

Learning outcome

On completion of the course, students will gain knowledge in:
•constructing and estimating appropriate statistical models for a particular business issue
•making critical business inferences from the data analysis
•using R to analyze data and interpret the results to gain insights

Upon completion of this course, students will be able to:
•apply data analytics to business problems
•derive actionable insights and recommendations for business managers
•use R to analyze business data


Typical subject areas covered are:
- Review of OLS (Ordinary Least Squares)
- Logistic regression and classification
- Factor/Principal component analysis
- Cluster analysis
- Tree-based models

Required prerequisite knowledge


Recommended previous knowledge

Appropriate bachelor background in core business fields as well as mathematics for business/economics and statistics for business/economics.Completed MØA103 before taking this course Basic knowledge of R if MØA103 is not completed   


Weight Duration Marks Aid
Written exam1/14 hoursA - FDictionary.
Valid calculator.
The final grade is based on an individual in-class written (digital) exam. Students are required to attend at least 80% of the in-class group work sessions (2 x 2 hour sessions every week) to be eligible for taking the final exam. Students failing the final exam will be granted the opportunity of taking a deferred exam in the same format.

Coursework requirements

Attendance at least 80% of the in-class group work session
Students are required to attend at least 80% of the in-class group work sessions (2 x 2 hour sessions every week) to be eligible for taking the final exam.

Course teacher(s)

Course coordinator
Yuko Onozaka
Course teacher
Tom Brokel , Espen Olsen , Elisa Thomas

Method of work

In this course, you will learn through the mixture of traditional lectures, group work, seminars, and individual study. Lectures provide the basic theoretical knowledge behind the methods. Both the group work and seminars are problem-based, and students will learn through estimating models by programming and running R and through interactions with team members and the instructor(s). Students are required to obtain necessary knowledge by self-studying different materials including videos, text book chapters, and lecture slides.
Expectations: 280 ECTS work hours divided on lectures, in-class and out-of-class group work, seminars and independent study.

Open to

Business Administration - Master of Science

Course assessment

Students will have the opportunity to give feedback on the course first in an early dialogue, and then in a written course evaluation at the end of the course.


Literatur will be published as soon as it has been prepared by the course coordinator/teacher

This is the study programme for 2020/2021.

Sist oppdatert: 11.03.2020