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Establishment
Language of instruction
English
Teaching content
MARKETING
This course occurs in the following program(s)
IESEG Degree - Programme Grande École
- Crédits ECTS: 2.00
Training officer(s)
S.NASINI
Présentation
Prerequisite
Thi course has two important prerequisite:
- Student have complete the Data Camp course Introduction to R before the start of the course, and show the obtained certificate to the professor (failing to obtain this certificate before the start of the course will imply a zero grade in the Individual Assignment).
- Students are expected to have completed a basic course in Statistics and/or Data Analysis.
- Student have complete the Data Camp course Introduction to R before the start of the course, and show the obtained certificate to the professor (failing to obtain this certificate before the start of the course will imply a zero grade in the Individual Assignment).
- Students are expected to have completed a basic course in Statistics and/or Data Analysis.
Goal
1) Understanding the main methodologies for data analysis.
2) Understanding the idea of statistical modeling to assess business decisions.
3) Selecting among datamining techniques to estimate the impact of business strategies.
2) Understanding the idea of statistical modeling to assess business decisions.
3) Selecting among datamining techniques to estimate the impact of business strategies.
Presentation
This is a course in datamining, whose main content is the statistical modelling and analysis applied to business data. The couse is designed to enable students to correctly assess business strategies, based on the use of statistical methods, supporting decision makers to select the optimal strategy under a variety of market conditions. In particular, the course introduces the students to data selection, inferential statistics, regression analysis and cluster analysis, which allow estimating the impact of business strategies on sales and forecasting the impact of future strategies. Statistical software, such as R, SAS and Excel, are used to study empirical cases.
Modalités
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours magistral | 16,00 | ||
| Cours interactif | 8,00 | ||
| Autoformation | |||
| Lecture du manuel de référence | 8,00 | From the list of recommended reading | |
| E-Learning | 8,00 | ||
| Travail personnel | |||
| Group Project | 8,00 | Students are assigned to small groups | |
| Overall student workload | 48,00 | ||
Evaluation
The students evaluation is based on an individual assignment (the Data Camp certificate) and a group project.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Participation | 0,00 | 0 | 20,00 |
| Autres | |||
| Projet Collectif | 8,00 | 1 | 40,00 |
| Projet Individuel | 8,00 | 1 | 40,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliography
Gerald J. Tellis, Chapter 24, Modeling Marketing Mix, publisher University of Southern California Online available at www-bcf.usc.edu/~tellis/mix.pdf -
Consumer Theory: http://www.columbia.edu/~md3405/IM_CT.pdf -
Consumer Theory: http://www.columbia.edu/~md3405/IM_CT.pdf -