EBA 3610 Decision Modelling Using Spreadsheet
EBA 3610 Decision Modelling Using Spreadsheet
The course combines consideration of realistic decision-making problems with theory and methodologies in building and solving spreadsheet models. Examples from finance, marketing, supply chain and other business areas illustrate management science applications and solutions methods using spreadsheet tools widely used in most of the organizations.
During the course, students should have acquired:
- Basic knowledge in Spreadsheet Modeling.
- Basic knowledge of Optimization with Linear, as well as Nonlinear Programming Models.
- Basic knowledge in Queueing Models.
After completing the course, students shall be able to:
- Identify and apply modelling approach to solve decision problems.
- Use spreadsheets for various business applications.
- Model and solve LP Problems and sensitivity analysis.
- Model decisions under uncertainty.
The students will learn how to analyze a decision problem, evaluate the data and how to select a modelling and solution approach.
- Introduction to Spreadsheet Modeling.
- IIntroduction to Optimization and Linear Programming Models.
- Modeling and solving LP Problems and sensitivity analysis.
- Network Models.
- Optimization Models with Integer Variables.
- Nonlinear Optimization Models.
- Solution methods: Simplex and Evolutionary Solver.
- Decision Making Under Uncertainty.
- Introduction to Simulations.
- Queueing Models.
- Regression and Forecasting Models.
- Multiobjective Decision Making.
- Inventory and Supply Chain Models.
The course will include/entail a combination of Lectures and exercises using Excel.
Students are expected to solve a number of spreadsheet exercises, which will be given after each lecture.
There will be a re-sit examination in EBA 36101 autumn 2022 and last time spring 2023.
Higher Education Entrance Qualification
Covid-19
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
Teaching
Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.
EBA 2910 Mathematics for Business Analytics, EBA 2904 Statistics or equivalent courses.
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Invigilation Weight: 100 Grouping: Individual Support materials:
Duration: 4 Hour(s) Exam code: EBA 36101 Grading scale: ECTS Resit: Examination every semester |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 45 Hour(s) | |
Group work / Assignments | 96 Hour(s) | |
Student's own work with learning resources | 55 Hour(s) | |
Examination | 4 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.
23/09/2022 Please note that re-sit examination autumn 2022 will be arranged as a home exam, 4 hours.
25/01/2023 The same applies for the re-sit spring 2023.