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MIB - RESEARCH METHODS FOR BUSINESS

2017-2018

IESEG School of Management ( IÉSEG )

Code Cours :

1718-IÉSEG-MIB1S1S2-RES-MIBCE01UE

RESEARCH


Niveau Année de formation Période Langue d'enseignement 
MSc in International Business1S1S2English
Professeur(s) responsable(s)J.MAES
Intervenant(s)Johan Maes Elias Hadzilias

    Ce cours apparaît dans les formations suivantes :
  • IÉSEG > MIB > MIB > 3,00 ECTS

Pré requis

None.

Objectifs du cours

At the end of the course, the student should be able to :
- Master the collection and analysis of data in support of business decisions (AACSB);
- Produce and interpret graphical summaries of data;
- Describe basic characteristics of the data distribution;
- Produce and interpret numerical summary statistics;
- Understand properties of the normal curve;
- Graphically and numerically describe the relations between two quantitative variables;
- Interpret a correlation coefficient, r, and the coefficient of determination;
- Formulate and interpret null and alternative hypotheses;
- Fit simple linear regression models;
- Use simple and multiple linear regression models to predict the value of one variable based on the value of (an) associated variable(s);
- Fit and interpret interactions between independent variables;
- Develop a greater awareness about ESRS topics such as conducting research in a rigorous, responsible, and ethical way, collecting and treating data with all necessary caution and interpreting results with all necessary reservations.

Contenu du cours

The course is designed to immerse students into the principles of descriptive and inferential statistical
analyses in order to make students acquainted with the techniques on how to collect and analyze data and information in order to provide solutions to business problems and challenges. Through readings, lectures, in-class exercises, a dedicated software (SPSS), and a tailored online environment, this course addresses the collection, description, analysis and critical summary of data, including the concepts of frequency distribution, parameter estimation, hypothesis testing, and regression analyses.


Modalités d'enseignement

Organisation du cours

TypeNombre d'heuresRemarques
Face to face
Interactive class24,00  
Independent study
Group Project10,00  
Estimated personal workload25,00  
Independent work
Research6,00  
E-Learning10,00  
Charge de travail globale de l'étudiant75,00  

Méthodes pédagogiques

  • Presentation
  • E-learning
  • Research
  • Project work
  • Interactive class


Évaluation

The instructor expects students to actively participate and behave responsibly in the course sessions. The student is assessed on the course-based (online) MCQs, a group project including analysis exercises with SPSS and being able to explain the meaning of the findings hereon, and a final exam.

Type de ContrôleDuréeNombrePondération
Continuous assessment
QCM2,00525,00
Others
Group Project10,00115,00
Final Exam
Written exam2,00160,00
TOTAL     100,00


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