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IESEG School of Management ( IÉSEG )

Code Cours :



Niveau Année de formation Période Langue d'enseignement 
Professeur(s) responsable(s)M.BUISINE
Intervenant(s)Matthieu Buisine Jennifer Amar Iuliana Matei Marijn Verschelde Arnaud Rys Thomas Baudin Mamoudou Camara

Pré requis

Basic knowledge of Excel (graphs, formulas…)
Basic statistical knowledge: scatter Plots, mean, standard deviation, linear correlation
Reading a statistical table (Standard Normal, Student and Fisher Tables)
Inferential Statistics: hypothesis testing, confidence interval on the mean.

Objectifs du cours

At the end of the course, the student should be able to:
- Understand how econometrics are used in each functional area of business, select a relevant research question or thesis statement and choose a relevant model.
- Use the simple or multiple regression analysis to predict the value of a dependent variable, evaluate assumptions of the regression analysis and understand advantages and drawbacks of the Ordinary Least Squares method.
- Identify outliers or influential points, use a dummy variable.
- Use statistical software or an Excel statistical package.
- Build a relevant model: being able to linearize a model, select the most relevant variables and understand multicolinearity.
- Assess model quality using R², Fisher Test. Check OLS assumptions.

Contenu du cours

Chapter I Simple Linear Regression: basics on sampling, graphs, correlation and linearizing, the OLS, assess model quality: SCE, R², hypothesis of the SLR, checking assumptions using graphs, inference about the slope, confidence Intervals on the forecasted value
Chapter II: Multiple Linear Regression: the multiple regression model, F Test for overall significance, multiple Regression Assumptions, inference about the slope, Dummy variables
Chapter III: Multiple Regression Model Building: quadratic Regression Model, introduction to Logistic Models, model Building: stepwise, best subset, VIF…

Modalités d'enseignement

Organisation du cours

TypeNombre d'heuresRemarques
Face to face
Independent work
Reference manual 's readings6,00  
Independent study
Group Project10,00  
Estimated personal workload6,00  
Charge de travail globale de l'étudiant38,00  

Méthodes pédagogiques

  • Project work
  • Interactive class


Interractive lectures and Tutorial format. Lecture's understanding is assessed thanks to two MCQs
A final group project allows students to use all course materials with real life data sets.

Type de ContrôleDuréeNombrePondération
Continuous assessment
Group Project0,00140,00
Final Exam
Written exam1,50140,00
TOTAL     100,00


  • Basic Business Statistics, 12/E (Mark L. Berenson, David M. Levine, Timothy C. Krehbiel), Pearson, 2011 -

Ressources internet

* Informations non contractuelles et pouvant être soumises à modification
Vidéo : Un campus à vivre
Notre chaîne Youtube