CORE PROGRAMME
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Background courses
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To be able to have access to the other parts of the
programme, the student must prove that he has a sufficient basis in
Mathematics, English, Computer studies, Descriptive
Statistics, elements of Probability and Statistical Inference. The
skills required are equivalent to the content of the courses listed
below :
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ANGL1860 |
A préciser
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COPS1121 |
Information Technology and Multimedia[30h+15h] (4 credits) (in French)
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Jean-Pierre Couwenbergh, Thierry De Smedt, Marcel Lebrun
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SESP1111 |
Statistics and Elements of Probability[37.5h+37.5h] (7 credits) (in French)
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Dominique Deprins, Annie Robert, Sébastien Van Bellegem
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ECGE1224 |
Economics and Management Statistics[30h+15h] (4 credits) (in French)
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Christian Hafner
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SESP1112 |
Mathematics and Logic[30h+15h] (3 credits) (in French)
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Etienne Loute, Yves Pochet
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ECGE1111 |
Mathematics and Analysis[30h+30h] (5 credits) (in French)
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Raouf Boucekkine, Yves Félix
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ECGE1214 |
Mathematics in Economics and Management[30h+15h] (4 credits) (in French)
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Raouf Boucekkine, Paul Henrard
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Any student possessing all of these
skills will be able to obtain 25 credits for their equivalence. All
lacks will have to be compensated for by following the appropriate
courses in agreement with the programme supervisor. The below-mentioned
course :
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STAT2400 |
Introduction to probability and statistics. Mathematics for the statistician.[30h+30h] (12 credits) (in French)
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Johan Segers, Ingrid Van Keilegom
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is programmed as a personalised refresher course in
mathematics and statistics for those who already partially possess the above bases.
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Courses on methodology and
statistical tools
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The student will choose at least 25 credits from the following
courses or will have the equivalent skills validated :
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INGE1222 |
Multivariate Statistical Analysis[30h+15h] (4 credits) (in French)
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Léopold Simar, François Vandenhende (supplée Léopold Simar)
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STAT2430 |
Statistical computing[20h+20h] (7 credits) (in French)
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Bernadette Govaerts
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STAT2410 |
Discrete data analysis.[22.5h+7.5h] (5 credits) (in French)
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Patrick Bogaert
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STAT2411 |
Data Analysis[22.5h+7.5h] (5 credits) (in French)
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Isabelle De Macq (supplée Léopold Simar), Léopold Simar
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STAT2412 |
Linear models[22.5h+7.5h] (5 credits) (in French)
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Christian Hafner
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STAT2413 |
Non parametric statistics[22.5h+7.5h] (5 credits) (in French)
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Ingrid Van Keilegom
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STAT2414 |
Times series[22.5h+7.5h] (5 credits) (in French)
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Rainer von Sachs
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STAT2415 |
Introduction to Bayesian statistics.[15h] (2.5 credits) (in French)
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N.
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STAT2416 |
Multivariate probabilities ans statistics[10h+5h] (2.5 credits) (in French)
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Ingrid Van Keilegom
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Project
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The student will complete, together with the
collaboration of an advisor, either a personal project to do with the
analysis of a statistics methodology problem, or a piece of work
involving the application statistics in the domain of the chosen
specialisation. The project may relate to an apprenticeship
in a company, the written work in that case taking the form of a report
on that experience. The project counts for 15 credits of the programme.
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Other courses
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The student will complete his programme with relevant
courses in the context of the master's of Statistics and the chosen
specialisation, of which the statistics lectures will constitute a
minimum of 10 credits.
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SPECIALISATIONS
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To complement the core programme, the student will
establish a programme of 30 credits in one of the below-mentioned
specialiations. He will select at least 15 credits of studies from the
courses listed and will complete this by means of lectures from a
domain of application related to the specialisation selected.
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Specialisation : Sciences and Technology
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BIRA2101 |
Biometry : analysis of the variance[30h+22.5h] (4 credits) (in French)
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Christian Hafner, Éric Le Boulengé
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BIRC2106 |
Chemometrics[22.5h+15h] (3 credits) (in French)
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Bernadette Govaerts
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BIRE2101 |
Statistical analysis of spatial and temporal data[22.5h+15h] (3 credits) (in French)
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Patrick Bogaert
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INMA2470 |
Discrete stochastic models[30h+22.5h] (5 credits) (in French)
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Philippe Chevalier
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MECA2646 |
Reliability and probabilistic risk analysis.[30h] (3 credits) (in French)
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Yves Smeers
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ESP3142 |
Epidemiology[22.5h+7.5h] (3 credits) (in French)
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Yves Coppieters 't Wallant
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STAT2510 |
Statistical quality control.[15h] (2.5 credits) (in French)
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Bernadette Govaerts
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STAT2520 |
Design of experiment.[22.5h+7.5h] (5 credits) (in French)
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Bernadette Govaerts, Éric Le Boulengé
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STAT2530 |
Statistics in clinical trials.[22.5h+7.5h] (5 credits) (in French)
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Annie Robert
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Specialisation : Economics and Insurances
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ACTU2111 |
Non life Insurance I[30h+15h] (4.5 credits) (in French)
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Antoine Delwarde (supplée Michel Denuit), Antoine Delwarde (supplée Michel Denuit), Michel Denuit
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ACTU2123 |
Non life Insurance II[30h] (4.5 credits) (in French)
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Michel Denuit
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ECON2135 |
Econometrics: methods and applications[45h+45h] (12 credits) (in French)
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Luc Bauwens
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ECON2245 |
Econometrics[30h+15h] (4 credits) (in French)
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Luc Bauwens
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STAT2550 |
Data Mining[15h+15h] (5 credits) (in French)
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Libei Chen
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Specialisation: Marketing and Surveys
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Compulsory course
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STAT2540 |
Survey and Sampling[15h] (2.5 credits) (in French)
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Yves Berger
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Other courses
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ACTU2111 |
Non life Insurance I[30h+15h] (4.5 credits) (in French)
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Antoine Delwarde (supplée Michel Denuit), Antoine Delwarde (supplée Michel Denuit), Michel Denuit
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DEMO3422 |
Theory and practice of surveys[20h] (3 credits) (in French)
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Claude-Michel Loriaux
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MARK2200 |
Market research[30h] (5 credits) (in French)
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Ruben Alberto Chumpitaz Caceres (supplée Marie-Paule Kestemont), Marie-Paule Kestemont, Claudine Laperche
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STAT2550 |
Data Mining[15h+15h] (5 credits) (in French)
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Libei Chen
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Specialisation : Mathematical Methods
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Compulsory course
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MATH2440 |
Statistical analysis[30h+22.5h] (5 credits) (in French)
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Ingrid Van Keilegom, Rainer von Sachs
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Other courses
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INMA2470 |
Discrete stochastic models[30h+22.5h] (5 credits) (in French)
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Philippe Chevalier
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INMA2471 |
Optimization models and methods[30h+22.5h] (5 credits) (in French)
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François Glineur
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INMA1170 |
Numerical analysis[22.5h+30h] (5 credits) (in French)
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Pierre-Antoine Absil, Paul Van Dooren, Paul Van Dooren
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MATH2360 |
Stochastic processes (statistics)[30h] (3.5 credits) (in French)
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Jean-Marie Rolin
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MATH2430A |
A préciser (in French)
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Specialisation : Data Management and Data Mining
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Compulsory courses
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STAT2550 |
Data Mining[15h+15h] (5 credits) (in French)
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Libei Chen
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STAT2560A |
Programmation de base en SAS[10h] (6 credits) (in French)
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N.
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STAT2560B |
Programmation avancée en SAS[40h] (6 credits) (in French)
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N.
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Additional recommended course
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INGI2271 |
A préciser (in French)
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In order to enrol for this specialisation, the student
must prove he has sufficient knowledge in English as the lectures and
exams linked to the seminar on data-management (STAT2560) are in
English. In addition to the UCL certification, part A of this seminar
enables the student to acquire the "SAS" certificate of "Base
programmer, " highly valued by firms. The part B seminar on data
management (STAT2560B) is only obtainable if the student succeeds in
attaining the certificate. Any student who does not succeed will have
to change his specialisation.
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Practical measures destined for students who are professionally active :
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The programme also caters for people who are
professionally active. It may, in fact, be spread over 2 to 4 academic years
and take the form of one, or sometimes two, days of lectures per week.
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A web-site has also been set up to make the
documents and instructions, linked to the various lectures, available
to the students :
http://www.stat.ucl.ac.be/diploma/coursmemoires.html
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Information from the secretary's office is communicated by
e-mail
issec@stat.ucl.ac.be
as well as on the web-site : (
http://www.stat.ucl.ac.be/diploma/infosetud.html
and students may also carry out certain administrative formalities by the same means.
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Last but not least, the students may acquire personal licences for the principal softeware
(SAS, S-Plus and SPSS) used during the master's programme.
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Positioning of the programme within the University cursus
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The master's of Statistics will enable the student to
acquire the necessary basics to embark on an in-depth studies degree in
statistics (DEA), possibly followed by a PHD (doctorat).
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