Courses Exchange Display 2015-2016
| Course Description | To PDF | |||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Course title | Business Analysis | |||||||||||||||||||||||||||||||||||||||||||||||
| Course code | EBC4104 | |||||||||||||||||||||||||||||||||||||||||||||||
| ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||||||||||
| Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||||||||||
| Period |
|
|||||||||||||||||||||||||||||||||||||||||||||||
| Level | Advanced | |||||||||||||||||||||||||||||||||||||||||||||||
| Coordinator |
Alexander Grigoriev, Mathias Staudigl For more information: a.grigoriev@maastrichtuniversity.nl; m.staudigl@maastrichtuniversity.nl |
|||||||||||||||||||||||||||||||||||||||||||||||
| Language of instruction | English | |||||||||||||||||||||||||||||||||||||||||||||||
| Goals |
Knowledge of crucial theoretical tools for analysing the data and managerial decision making. Ability to translate a verbal fuzzy description of a business problem into the mathematical model.
|
|||||||||||||||||||||||||||||||||||||||||||||||
| Description |
This course deals with a toolbox from econometrics and applied operations research. Particularly, the following quantitative methods are extensively discussed:
1. Forecasting 2. Regression analysis 3. Time series 4. Linear programming 5. Integer linear programming 6. Simulations 7. Multiobjective optimization Besides, students learn how to read manuscripts on the level of current scientific standards, and give presentations using the advanced quantitative reasoning in managerial decision making. |
|||||||||||||||||||||||||||||||||||||||||||||||
| Literature |
J.E. Hanke and D.W. Wichern, Business forecasting, International Edition, Pearson Education.
C.T. Ragsdale, Managerial Decision Modeling, Thomson South-Western. Research papers. |
|||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites |
Moderate mathematical and statistical skills and ability to understand quantitative models and concepts.
An advanced level of English. |
|||||||||||||||||||||||||||||||||||||||||||||||
| Teaching methods (indicative; course manual is definitive) | PBL / Presentation / Assignment / Papers / Groupwork | |||||||||||||||||||||||||||||||||||||||||||||||
| Assessment methods (indicative; course manual is definitive) | Final Paper / Participation / Written Exam | |||||||||||||||||||||||||||||||||||||||||||||||
| Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||||||||||
| This course belongs to the following programmes / specialisations |
|