Study Programmes 2016-2017
| STAT0067-4 | |||||
| Probability and statistical inference | |||||
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Duration :
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| 50h Th, 15h Pr | |||||
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Number of credits :
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Lecturer :
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| Louis Esch | |||||
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Language(s) of instruction :
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| French language | |||||
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Organisation and examination :
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| Teaching in the second semester | |||||
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Units courses prerequisite and corequisite :
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| Prerequisite or corequisite units are presented within each program | |||||
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Learning unit contents :
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| 1st part : Probability Theory
- Random situations, events and probability - Conditioning, probability trees and independance - Random variables and probability distribution - Typical parameters and moments of r.v. - Stochastic convergences - Theoretical distributions I (discrete laws, continuous laws and limit theorems) - Multivariate r.v. - Moments of multivariate r.v. - Stochastic processes - Applications 2nd part : Statistical inference - Introduction (object, variables, observations, population and sample) - Sampling and sampling distribution - Theoretical distributions II - Point estimation (estimators : properties and construction) - Confidence interval estimation - Statistical tests (principle and power, conformity and comparison, non parametrical tests) - Inference for regression |
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Learning outcomes of the learning unit :
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| - Allow to understand probability calculus and to modelize random situations
- Provide probabilistic basics useful for statistical inference, operational research and financial and actuarial applications)
- Allow to use principles and basic methods of statistical inference (estimation and tests)
In a general way, this course will allow to reach the following learning objectives : - Strategy : The course will allow students to demonstrate scientific precision and a critical mind in the analysis of a complex situation. - Implementation : The course will train the student to capitalize on the characteristics of a more and more digitalized world when confronted with a complex situation. - Adaptability : The course will encourage students to be creative, self sufficient and full of entrepreneurial spirit in their studies as well as in their professional life. |
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Prerequisite knowledge and skills :
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| - Descriptive statistics - Elements of differential and integral calculus |
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Planned learning activities and teaching methods :
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Mode of delivery (face-to-face ; distance-learning) :
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| - Ex-cathedra lectures (theory) - Exercises with groups |
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Recommended or required readings :
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| Copy of slides
Reference books - ROSS S.M., Initiation à la théorie des probabilités, Presses polytechniques romandes - DROESBEKE J.J., Eléments de statistique, Ellipses |
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Assessment methods and criteria :
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| Written examination, 1st and 2nd sessions | |||||
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Work placement(s) :
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Organizational remarks :
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Contacts :
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| Professor
Louis Esch HEC-Ecole de gestion de l'Université de Liège (bâtiment N1) Tél. : 04/232.73.00 e-mail : louis.esch@ulg.ac.be Teaching assistants S. Maron, Bât. N1, Local 306. Tél. : 04 232 73 01 e-mail : Sabine.Maron@ulg.ac.be M.-C. Cillis, Bât. N1, Local 306. Tél. : 04 232 73 41 e-mail : mccillis@ulg.ac.be |
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Items online :
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 | syllabus theory and exercises |
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