Study Programmes 2015-2016
STAT1208-2  
Probability and statistical inference
Duration :
50h Th, 15h Pr
Number of credits :
Bachelor in business engineering6
Lecturer :
Cédric Heuchenne
Language(s) of instruction :
French language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Course contents :
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.
Learning outcomes of the course :
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.
Prerequisite knowledge and skills :
Basic probability, Kolmogorov's axioms, conditional probabilities. This content is included in the course: STAT0003-1 Descriptive Statistics.
Planned learning activities and teaching methods :
15h exercises.
Mode of delivery (face-to-face ; distance-learning) :
A1. Ex-cathedra classes (+ videos support).
A1. Study and comprehension of the course.
A2. Supervised exercises. A teaching assistant supervises students solving exercises individually during programmed sessions. Supplementary exercises are placed at the disposal of students.
Recommended or required readings :
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.
Assessment methods and criteria :
Written exams in the first and second sessions (about the whole course -50% of the final mark about theoretical concepts and 50% exercices-).
Student evaluation is strictly individual.
Work placement(s) :
Organizational remarks :
Teaching language: French
Contacts :
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
Items online :
course material
syllabus, slides, list of exercises, videos