ØKA201 Data analysis and programming for economists (Spring 2027)

Facts about the course

ECTS Credits:
10
Responsible faculty:
Faculty of Computer Sciences, Engineering and Economics
Campus:
Halden
Course Leaders:
  • Jørn Inge Halvorsen
  • Bjørnar Karlsen Kivedal
Teaching language:
English
Duration:
½ year

Table of contents

The course is affiliated to the following study programme

Compulsory for students on

  • the Bachelor Programme in Business Administration specializing in International Business
  • the Bachelor Programme in Business Administration specializing in Economic Analysis

Elective for students on

  • the Bachelor Programme in Accounting
  • the Bachelor Programme in Business Administration specializing in Economics and Management

Recommended previous knowledge

ØKA120 Statistics and research methodology, or equivalent

Teaching semester

6th semester (spring)

10th semester (spring) for part-time students

Content

Programming:

  • Basic programming skills useful for applied statistics and econometric analysis and for writing advanced technical reports

Applied statistics and econometrics:

  • Regression analysis and other analytical tools used in applied statistics and econometrics

The student's learning outcomes on passing the course

This subject will enable the student to achieve the following learning outcomes.

Knowledge

  • The student will have gained knowledge of basic programming skills for the creation and understanding of functions and libraries, manipulation of data, visualizations and writing and editing technical reports that consist of both code and text.
  • Perform and analyze regression analysis and other analytical tools used in applied statistics and econometrics

Skills

  • Analyze data both related to data visualization and descriptive statistics
  • The creation of fully reproducible technical reports that consists of both code and text
  • Perform regression analysis and use other statistical tools, as well as analyzing results

General competence

  • The student will be able to handle small and big data sets, as well as using tools to perform and interpret analyses

Teaching and learning methods

Students will participate in the following learning activities:

Lectures, seminars, group work, and group discussions and presentations.

Workload

The course will give the student approximately 280 hours of work.

Coursework requirements - conditions for taking the exam

Group or individual written assignment(s) will be assessed on a pass/fail basis. The assignment(s) needs to be passed in order to obtain permission to take the final exam.

Exam

Individual written examination on campus Four hours individual written examination on campus. Aids allowed: - calculator with empty memory, incapable of symbolic computation or wireless communication - formula list (attached to the assignment) Grades: A-F.

Examiners

Internal or external examination

Course evaluation

To improve the course, we need the evaluations from the students. The course is evaluated eachsemester. The evaluations from the students are treated by the by the departement staff.

Reading list

The current reading list for 2024 Spring can be found in Leganto
Last updated from FS (Felles studentsystem) Oct. 15, 2026 4:26:27 AM