Calcul des probabilités et statistiques

Descriptive statisitics (1 and 2 dimensions). Probability axioms. Random variables. Combination of random variables. Typical random variables. Fundamental theorems. Statistical inference. Introduction to linear programming.

After completing this teaching unit the student will manage the basic concepts of probabilty and statistics (including some elements of operational research). He will be able to perform an exploratory data analysis, to model simple stochastic problems with particular random variables and to understand key concepts of statistical inference (hypothesis testing and confidence intervals).

Lectures and exercices.

Contribution to the teaching profile

Be capable of formulating and solving complex or open-ended technical and scientific problems by using abstraction, modeling, simulation, and multi-disciplinary analysis while satisfying the requirements of university-level research and responding to requirements, constraints, the set context and the technical, socio-economical ethical and environmental stakes—all with the purpose of obtaining concrete solutions. Innovate, by combining rigor and creativity, using a critical and demanding scientifical methodology (including state-of-the-art, problem statement, fixing hypothesis, modeling, validation, argumentation, and peer-review).

References, bibliography, and recommended reading

"Probability and Statistics for Engineers and Scientists" Walpole, Myers, Myers, Ye, Pearson International Edition, 8th edition

Course notes

• Podcast
• Syllabus
• Université virtuelle

Contacts

Prof. Yves De Smet

02.650.59.57 - yves.de.smet@ulb.ac.be

2N3 216

Campus

Solbosch

Method(s) of evaluation

• written examination

written examination

Written exam.

Mark calculation method (including weighting of intermediary marks)

Written exam: 3 questions on theory (50% of the final grade), 3 questions on exercices (50% of the final grade) - an additional question about operations research.

Language(s) of evaluation

• french