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IESEG School of Management ( IÉSEG )

Code Cours :



Niveau Année de formation Période Langue d'enseignement 
Professeur(s) responsable(s)T.TESSITORE , C.JANSSEN
Intervenant(s)Catherine JANSSEN, Tina TESSITORE, Romain CADARIO

Pré requis

Students should be knowledgeable about basic concepts in statistics. Some knowledge of Marketing Research is also recommended.

Objectifs du cours

At the end of the course, the student should be able to :
1. Have a deeper understanding of the different data analysis techniques available;
2. Understand the use of these different data analysis techniques for marketing-oriented research and business problems;
3. Identify the relevant statistical test(s) to perform;
4. Apply the different data analysis techniques and interpret the results of statistical outputs;
5. Know how to use a data analysis software such as SPSS.
6. Be able to communicate about and present statistical results in a clear and proper way.

Contenu du cours

The course of Advanced Data Analysis focuses on different data analysis techniques, that will be applied in a marketing context. Students will learn when and how to use these different techniques, as well as how to report and present results of statistical analyses in a professional manner.
To get acquainted to this, students will perform several exercices in class using the data analysis software SPSS (in-class assignments), and solve a challenging business case in groups based on real-life data (group project). The course focuses on the application of data analysis techniques for real business purposes, and more specifically, marketing-oriented ones.
The course will cover the following topics: Introduction to the SPSS environment (data preparation, dealing with missing data, exploring data with graphs…), hypothesis testing, descriptive analysis, statistical tests (Chi-square, T-Test, ANOVA…).

Modalités d'enseignement

Organisation du cours

TypeNombre d'heuresRemarques
Face to face
Interactive class8,00   The 16 course hours will be used for both interactive sessions (theory and examples) and in-class exercices, during which active participation from students is expected.
Tutorials8,00   In-class exercises, which consist of the (supervised) application of the theory to research-oriented examples and preparation for the group project.
Independent study
Group Project28,00   Group project, that will be the object of a presentation and preparation of a written report
Estimated personal workload6,00  
Charge de travail globale de l'étudiant50,00  

Méthodes pédagogiques

  • Tutorial
  • Presentation
  • Project work
  • Interactive class


Students will be evaluated based on:
- Class participation
- In-class exercises done during each course session. In these exercices, students will have to apply the data exploration and analysis techniques covered in class.
- Group project: students will execute the analysis of real business data. Deliverables include a written management report and a group presentation
- Final exam

Type de ContrôleDuréeNombrePondération
Continuous assessment
Continuous assessment0,00025,00
Group Project0,00150,00
Final Exam
Written exam2,00125,00
TOTAL     100,00


  • Recommanded book: Andy Field (2013), "Discovering statistics using IBM SPSS Statistics", Sage. -

  • Recommended book: Charry et al. (2016), "Marketing research with IBM SPSS Statisitcs: A practical guide", Routledge. -

Ressources internet

  • IESEG Online

    The couse website will be used to make the slides of the course, class exercices, and materials for the group project available to students.

* Informations non contractuelles et pouvant être soumises à modification
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