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| STAT1208-2 | Probability and statistical inference
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| Duration : | 50h Th, 15h Pr |
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| Number of credits : |
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| Lecturer : | Cédric Heuchenne |
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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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| All year long, with partial in January |
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Course contents :
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| The course is divided into two parts. The first one introduces random quantities on the basis of basic probability concepts and the second one describes statistical inference in a general way. In the first part, we explain how some phenomena can be described by random variables (discrete, continuous, uni- and multivariate) and their standard quantities. Next, usual discrete and continuous laws for random variables and vectors are developed. In the second part, the concept of sample taken from a population is introduced. We focus on the fact that a statistic constructed from the sample is a basis for statistical inference. Its distribution enables to evaluate precision of pointwise estimators, to build confidence intervals and to control error risk when testing hypothesis. |
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Learning outcomes of the course :
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| This course is a prerequisite for other courses teached later in the program. Indeed, a number of quantitative methods in management is based on concepts introduced in this course. Thus, the student should be able to understand and handle probability and statistics basic concepts.
Intended key learning outcomes of the program
Being able to use accounting, mathematical, statistical and IT tools to solve a management problem
Moreover, this course can be considered as a toolbox to further understand and handle other intended key learning outcomes, especially,
- knowing and understanding the basic theories and principles governing the main functions of a firm: marketing, HRM, finance and supply chain management
- knowing and understanding the main theories, their sequence and structure, in terms of political economics, micro and macro economics and industrial economics.
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Basic probability, Kolmogorov's axioms, conditional probabilities. This content is included in the course: STAT0003-1 Descriptive Statistics. |
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Planned learning activities and teaching methods :
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| 15h exercises during both semesters. |
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Mode of delivery (face-to-face ; distance-learning) :
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| A1. Ex-cathedra classes during both semesters of the academic year.
A1. Study and comprehension of the course.
A2. Supervised exercises during the whole year. A teaching assistant supervises students solving exercises individually during programmed sessions. Supplementary exercises are placed at the disposal of students. |
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Recommended or required readings :
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| Learning material (for the exam):
syllabus, slides used during the theoretical lectures, videos and exercises lists.
Advised books:
-Droesbeke J-J. (1997), Eléments de Statistique, 3e édition, Editions de l'Université de Bruxelles/Editions Ellipses.
-Lecoutre J-P. (1998), Statistique et Probabilités, Dunod.
-Saporta G. (1990), Probabilités, Analyse des Données et Statistique, Editions Technip. |
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Assessment methods and criteria :
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| Written exams in the first and second sessions (about the whole course -50% of the final mark about theoretical concepts and 50% exercices-). Moreover, a written test about the first part of the course is organized in January (-50% of the mark about theoretical concepts and 50% exercices-): its weight in the final 1st session note is 50%.
Student evaluation is strictly individual. |
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Work placement(s) :
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Organizational remarks :
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| Teaching language: French |
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Contacts :
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| Cédric HEUCHENNE, HEC-ULg Management School of the University of Liège, N1, local 309, email: C.Heuchenne@ulg.ac.be
Alessandro BERETTA, HEC-ULg Management School of the University of Liège, N1, local 310, email: A.Beretta@ulg.ac.be |
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| Items online : |
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| course material |
| syllabus, slides, list of exercises, videos |
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