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2016/2017  KAN-CCMVV1401U  Business Analytics and Decision Making

English Title
Business Analytics and Decision Making

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course Third Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Dolores Romero Morales - Department of Economics (ECON)
Kontaktinformation: https:/​/​e-campus.dk/​studium/​kontakt eller Contact information: https:/​/​e-campus.dk/​studium/​kontakt
Main academic disciplines
  • Finance
  • Economics
Last updated on 05-04-2016
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors: After completing this course, the students should be able to:
  • Display knowledge of Multivariate Statistical Theory, especially Regression Analysis in Decision Making, and apply this knowledge in areas such as Business Forecasting
  • Display knowledge of Optimization Theory as it pertains to Decision Making, and apply this knowledge in areas such as Portfolio Optimization
  • Display knowledge of Risk Analysis in Decision Making, such as in Financial Investment
  • Demonstrate awareness of the application of Decision Analysis in Decision Making, such as in Project Management
  • Be confident users of package computer programs that are widely used in industry for Regression Analysis, Optimization, Decision Analysis and Risk Analysis
  • Appreciate the wider implications of uncertainty in Decision Making and the related need for solutions that are both flexible and robust
Examination
Business Analytics and Decision Making:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Spring
Make-up exam/re-exam
Same examination form as the ordinary exam
* if the student fails the ordinary exam the course coordinator chooses whether the student will have to hand in a revised product for the re- take or a new project.
Course content and structure

In the current competitive environment, it is important to understand the relationships between different business factors, to forecast trends, to appreciate the risks arising from management actions, and to optimize investment strategies. Decisions are often taken under considerable uncertainty and time pressure. Therefore, managers need to be able to grasp the range of uncertainty rapidly and make rational decisions, which are both flexible and robust. Statistical and optimization theory provide an excellent basis to do this. This course aims to enhance your theoretical knowledge of and practical skills in modern Business Analytics tools. The course uses computer software to illustrate how to apply the methodologies we introduce. The course is multidisciplinary in nature with links to areas such as accounting, economics, finance, marketing, and operations management.

 

The course’s development of personal competences:

 

During the course, and through a hands-on approach supported by underlying statistical and optimization theory, students will develop quantitative skills needed for Decision Making, as well as learn to appreciate the implications of uncertainty in Decision Making and the need for flexible and robust solutions.

 
Teaching methods
Lectures, Exercises, Demos, Computer Workshops
Student workload
Preparation 101 hours
Classes 33 hours
Exam 72 hours
Further Information

Main academic disciplines

 

Statistical Analysis, Optimization, Economics, Finance, Operations, Marketing
Expected literature

Wisniewski, M. (2009), Quantitative methods for decision makers, 5th edn. FT Prentice Hall.

 

Albright, S.C., Winston, W.L. and Zappe, C. (2011), Data Analysis, Optimization, and Simulation Modeling (UK: Thomson Southwestern). 
Last updated on 05-04-2016