Study programme 2020-2021Français
Statistics and Econometrics for Business
Programme component of Master's in Business Engineering à la Warocqué School of Business and Economics

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
UW-M1-IGGEST-004-MCompulsory UEDHYNE EmmanuëlW718 - Analyse économique du travail
  • DHYNE Emmanuël

of instruction
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français301500055.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
W-AETR-005Statistics and Econometrics for Business3015000Q2100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Mobilise expertise in at least one area of management.
    • Master the principal decision-making processes of a company.
  • Professionally communicate and present original work both orally and in writing.
    • Conduct scientific reasoning on complex or innovative management issues.
  • In an active and integrated manner, master knowledge in the various fields of management and use them effectively in a professional context.
    • Integrate highly specialised knowledge in different fields of management.
  • Adopt a scientific approach of analysis and reasoning.
    • Master the different steps and methods to carry out research on complex or innovative management issues.
    • Construct a reference framework, formulate questions or hypotheses from the analysis of scientific literature.
    • Collect data, analyse it qualitatively and quantitatively and adequately interpret the results, taking into account the reference framework within which the research was developed.
  • Develop innovative strategies.
    • Mobilise the methods and management support tools in changing contexts.
    • Innovate in the development of methodologies and tools for analysis and decision-making in management.
  • Integrate scientific and technological processes.
    • Identify, model and analyse real and complex problems in management sciences.

Learning Outcomes of UE

At the end of this course, students will be able to apply a series of econometric tools (time series analysis, limited dependent variables)  useful for empirical analysis in the field of management. Students will also learn how to use the software Stata.

Content of UE

Univariate and multivariate time series analysis : ARMA, unit root and stationarity tests, VAR, ARCH and GARCH models, ... Cross-sectional data (probit, logit) and panel data analysis.

Prior Experience

matrix calculus, probality and statistical inference, OLS, Stata Statistics I and II, Econometrics I

Type of Assessment for UE in Q2

  • Presentation and/or works
  • Oral Examination
  • Written examination

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

  • Oral examination
  • Written examination

Q3 UE Assessment Comments

Based on the number of students, written or oral examination

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
  • Cours magistraux
  • Conférences
  • Travaux pratiques
  • Travaux de laboratoire
  • Exercices de création et recherche en atelier
  • Projet sur ordinateur
  • Etudes de cas

Mode of delivery

AAMode of delivery
  • Mixed

Required Reading


Required Learning Resources/Tools

AARequired Learning Resources/Tools
W-AETR-005Not applicable

Recommended Reading


Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
W-AETR-005Not applicable

Other Recommended Reading

AAOther Recommended Reading
W-AETR-005Chris Brook " Introductory econometrics for finance ", Cambridge University Press Michel Tenenhaus : "Statistique : méthodes pour décrire, expliquer et prévoir"

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 09/07/2021
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