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English
Teaching content
QUANTITATIVE METHODS
Training officer(s)
M.VARDANYAN
Stakeholder(s)
M.VARDANYAN
Présentation
Prerequisite
Working knowledge of algebra
Goal
Quantify relationships among various economic/business variables
Interpret estimation results and make predictions
Use statistical theory to test the reliability of results
Mitigate common problems that arise during econometric estimation
2.B Solve professional dilemmas using concepts of CSR and ethics
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 (QM AACSB Grade 5.D)
6.A Thoroughly examine a complex business situation
6.B Synthesize multifaceted information from various sources across different functional fields (QM AACSB Grade 6.B)
6.D Combine new knowledge with hands-on experiences and experiential projects to address organizational challenges
Interpret estimation results and make predictions
Use statistical theory to test the reliability of results
Mitigate common problems that arise during econometric estimation
2.B Solve professional dilemmas using concepts of CSR and ethics
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 (QM AACSB Grade 5.D)
6.A Thoroughly examine a complex business situation
6.B Synthesize multifaceted information from various sources across different functional fields (QM AACSB Grade 6.B)
6.D Combine new knowledge with hands-on experiences and experiential projects to address organizational challenges
Presentation
Regression analysis using Ordinary Least Squares
Using Excel to estimate regressions
Assessing the quality of estimation results
Making predictions about future outcomes
Modeling using alternative functional forms
Interpretation of estimation results
Hypothesis testing
Dealing with the problem of multicollinearity
Estimating logistic regressions using SAS
Using Excel to estimate regressions
Assessing the quality of estimation results
Making predictions about future outcomes
Modeling using alternative functional forms
Interpretation of estimation results
Hypothesis testing
Dealing with the problem of multicollinearity
Estimating logistic regressions using SAS
Modalités
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 24,00 | ||
| Autoformation | |||
| Lecture du manuel de référence | 5,00 | ||
| E-Learning | 5,00 | ||
| Recherche | 5,00 | ||
| Travail personnel | |||
| Group Project | 10,00 | ||
| Charge de travail personnel indicative | 26,00 | ||
| Overall student workload | 75,00 | ||
Evaluation
The students will work on a class project in groups of 3-4 students. They will present their work during the last session
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Participation | 24,00 | 1 | 10,00 |
| Autres | |||
| Projet Collectif | 10,00 | 1 | 45,00 |
| Examen (final) | |||
| Examen oral | 0,50 | 1 | 45,00 |
| TOTAL | 100,00 | ||