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Our Degree Programs
Establishment
Language of instruction
English
Teaching content
QUANTITATIVE METHODS
Training officer(s)
J.VAKKAYIL
Stakeholder(s)
Marouen BEN JEBARA
Présentation
Prerequisite
Working knowledge of algebra and basic statistics:
• Data exploration and visualization
• Descriptive statistical measures
• Probability distributions
• Data exploration and visualization
• Descriptive statistical measures
• Probability distributions
Goal
3.A Breakdown complex organizational problems using the appropriate methodology
5.B Construct expert knowledge from cutting-edge information
5.D. Make effectual organizational decisions
6.A Thoroughly examine a complex business situation
6.B Synthesize multifaceted information from various sources across different functional fields
1. Use data-driven approaches to develop Predictive Analytics models
2. Develop, implement, and analyze Monte Carlo Simulation models
3. Develop, implement and analyze Prescriptive Analytics models
4. Apply the most common tools in decision analysis with uncertain consequences
5. Use the Excel and tools to implement the methodologies mentioned above
5.B Construct expert knowledge from cutting-edge information
5.D. Make effectual organizational decisions
6.A Thoroughly examine a complex business situation
6.B Synthesize multifaceted information from various sources across different functional fields
1. Use data-driven approaches to develop Predictive Analytics models
2. Develop, implement, and analyze Monte Carlo Simulation models
3. Develop, implement and analyze Prescriptive Analytics models
4. Apply the most common tools in decision analysis with uncertain consequences
5. Use the Excel and tools to implement the methodologies mentioned above
Presentation
1. Spreadsheet modeling and analysis
2. Monte Carlo Simulation and risk analysis
3. Predictive Analytics using Excel
4. Prescriptive Analytics using Solver
5. Business applications of Predictive Analytics, Monte Carlo Simulation, and Prescriptive Analytics
2. Monte Carlo Simulation and risk analysis
3. Predictive Analytics using Excel
4. Prescriptive Analytics using Solver
5. Business applications of Predictive Analytics, Monte Carlo Simulation, and Prescriptive Analytics
Modalités
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 16,00 | ||
| Autoformation | |||
| Lecture du manuel de référence | 5,00 | ||
| Recherche | 4,00 | ||
| Travail personnel | |||
| Group Project | 15,00 | ||
| Charge de travail personnel indicative | 10,00 | ||
| Overall student workload | 50,00 | ||
Evaluation
The students will work on a class project in groups of 4-5 students. They will present their work during the last session. Student’s contribution to the group work will be evaluated using peer grading. The students will work on three case studies as well as individual assignments.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| QCM | 16,00 | 1 | 15,00 |
| Examen partiel | 1,00 | 1 | 15,00 |
| Autres | |||
| Etude de cas | 10,00 | 1 | 30,00 |
| Projet Collectif | 5,00 | 1 | 30,00 |
| Rapport écrit | 10,00 | 1 | 10,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliography
Business Analytics: methods, models, and decisions James R. Evans -