EPN-V2

ØABED2200 Business Analytics Course description

Course name in Norwegian
Business Analytics
Study programme
Bachelor Programme in Business Administration and Economics
Oslo Business School, Exchange Programme
Weight
7.5 ECTS
Year of study
2023/2024
Curriculum
SPRING 2024
Schedule
Course history

Introduction

Se programplanen.

Recommended preliminary courses

Mathematics, Statistics, Financial Accounting, Managerial Accounting.

Required preliminary courses

Studiearbeidet i emne 1 er hovedsakelig knyttet til utviklingen av grunnleggende ferdigheter, med vekt på muntlig engelsk. Dette inkluderer også kunnskap om vurdering av elevenes muntlige ferdigheter når det gjelder å lytte, tale og samtale. Det er satt fokus på utvikling av studentenes språkbevissthet og evne til å formidle faglig kunnskap i forskjellige typer tekst, både muntlige og digitale, med varierende grad av formalitet. Innsikt i flerspråklighet, tilpasset opplæring, og elevaktive og digitale læringsformer gjennomsyrer arbeidet med hovedtemaene. Studentene får en innføring i nyttige digitale verktøy og benytter dem selv i sitt studiearbeid, både i produksjon av tekst og til refleksjon.

Emne 1 fokuserer på:

  • engelsk som verdensspråk og flerspråklighet
  • utvikling av elevenes muntlige ferdigheter
  • grunnleggende mønstre i fonetikk og grammatikk

Learning outcomes

After completing the course, the student should have the following overall learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student has

  • knowledge of how to apply the methods Decision Theory, Linear Programming, Simulation, Prediction Models, and Data Mining to business decision problems.
  • knowledge of how quantitative methods and optimization can be used to solve business decision problems.

Skills

The student can

  • perform analysis of business decision problems and make decisions based on maximin, minimax, minimax and opportunity cost
  • draw decision trees and make decisions based on them
  • perform simple and multiple regression analysis using relevant software and interpret results
  • prepare forecasts using e.g. moving average, exponential smoothing and regression analysis
  • formulate problems that can be solved using linear programming, as well as assess shadow prices and the value of increased capacity
  • formulate and solve transport problems
  • use relevant computer tools to solve business decision making problems
  • implement simple simulation models in relevant computer tools
  • carry out data mining in relevant data tools

General competence

The student

  • has increased numerical and analytical competence
  • can reflect on ethical issues related to business decision-making
  • can solve problems in groups

Teaching and learning methods

Lectures and workshops solving cases in groups. Emphasis is placed on the use of computer tools in teaching.

Course requirements

The following coursework requirement must have been approved for the student to take the exam:

  • Coursework 1: 5 individual assignments. The student must pass at least 4 out of 5 assignments to take the exam. Each assignment consists of answering questions from a business case, and may also include quiz and contribution to discussion on the course website. Expected time to complete each assignment is 5 hours. Each assignment must be completed and approved by the given deadline.

The purpose of the coursework requirement is for the students to apply and evaluate analysis methods taught in the module.

All required coursework must be completed and approved in order for the student to take the exam. If the coursework requirement is not approved, the student is given one opportunity to submit an a new coursework requirement within a specified deadline.

Assessment

The exam in the course is an course paper written in groups of 3 or 4 students. The assignment has a scope of a maximum of 15 pages. Font and font size: Arial / Calibri 12 points. Line spacing: 1.5.

Permitted exam materials and equipment

All aids are permitted, as long as the rules for source referencing are complied with.

Grading scale

Grade scale A - F

Examiners

The exam papers are assessed by one internal and one external examiner.

At least 25% of the exam papers will be assessed by two examiners. The grades awarded for the papers assessed by two examiners form the basis for determining the level for all the exam papers.

Course contact person

Knut Nygaard