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Language of instruction
English
Teaching content
QUANTITATIVE METHODS
This course occurs in the following program(s)
IESEG Degree - Programme Grande École
- Crédits ECTS: 2.00
Training officer(s)
T.TESSITORE, C.JANSSEN
Stakeholder(s)
Catherine JANSSEN, Tina TESSITORE, Dorian ROULET, Goedele KREKELS
Présentation
Prerequisite
Students should be knowledgeable about basic concepts in statistics. Some knowledge of Marketing Research is also recommended.
Goal
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.
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.
Presentation
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…).
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
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 8,00 | 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. | |
| Travaux dirigés | 8,00 | In-class exercises, which consist of the (supervised) application of the theory to research-oriented examples and preparation for the group project. | |
| Travail personnel | |||
| Group Project | 28,00 | Group project, that will be the object of a presentation and preparation of a written report | |
| Charge de travail personnel indicative | 6,00 | ||
| Overall student workload | 50,00 | ||
Evaluation
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
- 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
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Contrôle continu | 0,00 | 0 | 25,00 |
| Autres | |||
| Projet Collectif | 0,00 | 1 | 50,00 |
| Examen (final) | |||
| Examen écrit | 2,00 | 1 | 25,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliography
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. -
Recommended book: Charry et al. (2016), "Marketing research with IBM SPSS Statisitcs: A practical guide", Routledge. -
Internet resources
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.