Table of contents

The course is connected to the following study programs

Teaching language

English

Prerequisites

Business Analytics 1 or equivalent

Learning outcomes

After completing this course, students should be able to:

  • Describe the general research process in a quantitative research project
  • Understand which research questions can be answered using quantitative method
  • Have knowledge about and understand the assumptions that linear regression analyzes are based on
  • Be able to perform and interpret linear regression analyzes using appropriate software
  • Understand the difference between correlation and causality
  • Be able to interpret and critically evaluate empirical research.

Contents

The main focus of Business Analytics 2 is to give students a thorough introduction to statistical analysis techniques used in econometrics. In the course, special emphasis will be placed on linear regression analysis and its extensions. Students will learn how the methods taught can be applied to analyze data using statistical program (STATA). The course builds on Business Analytics 1.

Teaching and learning methods

The course is taught through student-active lectures designed to promote dialogue, discussion, and student reflection. The teaching also includes elements of group work, Data Lab (STATA) and other student-active learning activities.

Attendance is mandatory, with a minimum requirement of 70% attendance. The course has an expected workload of approximately 200 hours. Guidelines for mandatory attendance can be found here: https://www.uia.no/english/about-uia/acts-and-regulations/guidelines-compulsory-attendance.html

Examination requirements

Approved compulsory assignments. More information will be provided at the start of the semester.

Examinations

3 hour written examination. Graded by letters.

Student evaluation

The person responsible for the course, in consultation with the student representative, decides the method of evaluation and whether the courses will have a midterm- or end of term evaluation, see also the Quality System, section 4.1. Information about evaluation method for the course will be posted on Canvas.
Last updated from FS (Felles studentsystem) Oct. 15, 2026 3:15:38 PM