Programplaner og emneplaner - Student
ØABED2200 Business Analytics Course description
- Course name in Norwegian
- Business Analytics
- Study programme
-
Bachelor Programme in Business Administration and EconomicsOslo Business School, Exchange Programme
- Weight
- 7.5 ECTS
- Year of study
- 2023/2024
- Curriculum
-
SPRING 2024
- Schedule
- Programme description
- 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