Statistics For Business and Economics (BØK356)

In the increasingly data-driven business environment, it is crucial for a modern business person to know how to utilize data. This course will teach you introductory statistics for business and economics students. The knowledge you acquire from this course will equip you with statistical literacy — a necessity to navigate through the digital world we live in today. Furthermore, the fundamental knowledge in statistics and programming serves as the absolute basis for a deeper understanding of concepts such as digital transformation, big data, machine learning, and artificial intelligence.

Course description for study year 2024-2025. Please note that changes may occur.


Course code




Credits (ECTS)


Semester tution start


Number of semesters


Exam semester


Language of instruction



Typical subject areas covered are:

  • Descriptive statistics
  • Probability
  • Combinatorics
  • Conditional probability
  • Random variables, mean, and variance
  • Joint distributions
  • Basic probability distributions
  • Estimation
  • Hypothesis testing
  • Linear Regression

Expectations: 300 ECTS work hours divided into lectures, computer (MS Excel and R programming) sessions, out-of-class work, exercises, and independent study.

Learning outcome


On completion of the course, students will gain knowledge in:

  • Utilizing fundamental statistical concepts, methods, and data to gain insights
  • Basic use of MS Excel
  • Basic programming in R


Upon completion of this course, students will be able to:

  • Describe data using summary statistics
  • Approximate real-world events with appropriate random variables and probability distributions
  • Master basic probability theory and probability models, combinatorics, sampling models, conditional probability, Bayes law, and independence of random variables.
  • Conduct hypothesis testing in binomial and multinomial models
  • Depict the relationship between and among variables using statistics, such as correlation and regression analysis
  • Run simple descriptive analysis in Excel
  • Import and export data into R
  • Use R to construct different measures and variables
  • Use R to conduct basic statistical analysis

Required prerequisite knowledge



Form of assessment Weight Duration Marks Aid
Written exam 1/1 6 Hours Letter grades

The final grade is based on a final individual exam counting for 100% of the grade.

Coursework requirements

Pass two individual quizzes
​​​​Students are required to pass 2 individual quizzes

Course teacher(s)

Course coordinator:

Yuko Onozaka

Course teacher:

Sufyan Ullah Khan

Study Program Director:

Tarjei Mandt Larsen

Method of work

In this course, you will learn through a mixture of traditional lectures, instruction videos, computer lab sessions, and individual study. Lectures provide the basic statistical concepts, while computer lab sessions will be problem-based in interactive and collaborative settings. There will be exercises provided for each topic covered.

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.


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