Actualités et agenda
Nos formations
Établissement
Langue d'enseignement
English
Matières
QUANTITATIVE METHODS
Ce cours apparaît dans les formation(s) suivante(s)
Diplôme IÉSEG (Bac +5) Programme Grande École
- Crédits ECTS: 2.00
Responsable(s)
M.Verschelde
Intervenant(s)
Balazs KOTOZS
Wanda MIMRA
Uyanga TURMUNKH
Marijn VERSCHELDE
Wanda MIMRA
Uyanga TURMUNKH
Marijn VERSCHELDE
Présentation
Prérequis
- Applying and analyzing linear regression models.
- Evaluating the assumptions of regression analysis and knowing what to do if the assumptions are violated.
- Creating a linear equation of a line using real data
- Explaining the meaning of the regression coefficients
- Making inferences about the slope and correlation coefficient
- Evaluating the assumptions of regression analysis and knowing what to do if the assumptions are violated.
- Creating a linear equation of a line using real data
- Explaining the meaning of the regression coefficients
- Making inferences about the slope and correlation coefficient
Objectifs
- Understand, identify and avoid common pitfalls when running a Linear Regression
- Recognize that caution is needed when we use Linear Regression when the dependent variable is a dummy
- Comprehend, apply and interpret discrete choice models
- Compare the quality of different discrete choice models
- Develop a project that concerns a quantitative analysis from scratch
- Evaluate the value of an existing analysis that concerns a quantitative analysis
- Recognize that caution is needed when we use Linear Regression when the dependent variable is a dummy
- Comprehend, apply and interpret discrete choice models
- Compare the quality of different discrete choice models
- Develop a project that concerns a quantitative analysis from scratch
- Evaluate the value of an existing analysis that concerns a quantitative analysis
Présentation
1. Introduction: the art of econometrics
2. The linear probability model
3. The Logit model
4. Model fit and various tests
2. The linear probability model
3. The Logit model
4. Model fit and various tests
Modalités
Organisation
| Type | Amount of time | Comment | |
|---|---|---|---|
| Autoformation | |||
| Recherche | 2,00 | ||
| Lecture du manuel de référence | 2,00 | ||
| Travail personnel | |||
| Individual Project | 30,00 | ||
| Présentiel | |||
| Cours interactif | 6,00 | ||
| Travaux dirigés | 4,00 | ||
| Coaching | 6,00 | ||
| Overall student workload | 50,00 | ||
Évaluation
• A classical final exam
• Involvement in-class and in the final project
• The project results
Respectively 30%, 35% and 35% of the final mark
Collective feedback will be provided on www.ieseg-online.com.
• Involvement in-class and in the final project
• The project results
Respectively 30%, 35% and 35% of the final mark
Collective feedback will be provided on www.ieseg-online.com.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Participation | 16,00 | 1 | 35,00 |
| Examen (final) | |||
| Examen écrit | 2,00 | 1 | 30,00 |
| Autres | |||
| Projet Individuel | 0,00 | 1 | 35,00 |
| TOTAL | 100,00 | ||