Business Analytics Data, Models and Decisions (BUSA)

Course description



Advances in information technology and quantitative methods have dramatically changed how modern firms operate. Many strategic and operational decisions are today based on models from operation management and management science. The objective of this course is to introduce the most important of these techniques and show how they can be used to make better decisions. Theory will be motivated by relevant examples with applications in operations, finance, management and marketing. Applications will be done using a common spreadsheet software (excel). The course will primarily be taught through lectures, computer labs and case discussions. Students will analyse cases and practice using data to make better and more informed decisions. The course will also highlight potential disadvantages and limitations of quantitative decision methods. The course will cover techniques such as decision analysis, decision trees, probability, statistics, econometrics, simulation, linear programming, non- linear optimization, and discrete optimization.



Intended Learning Outcomes

Upon completion of the course, students should be able to:

Knowledge and understanding
1. Recognize the underpinnings of quantitative decision methods.

Skills and abilities
2. Use data and models that can help businesses make better decisions.

Judgement and approach
3. Critically evaluate quantitative decision tools and their advantages and limitations.

Change semester  


Course title:
Business Analytics Data, Models and Decisions
Semester: Autumn term 2019
Study period: 2
Rate of studies: 100%
Level: Graduate level (second cycle)
Credits: 7.5
Language of instruction: English

Course code: FE5435

Syllabus

Contact:


Course coordinator:
Toivo Lepp
Head of course:
Olov Isaksson
Examiner:
Olov Isaksson
Student services:
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