ECTS
5 credits
Component
Faculty of Science
Description
This course introduces probability spaces, the concepts of probability and independence, and defines discrete and density random variables, with an emphasis on modeling.
Objectives
Probabilized spaces.
Random experiments. Events. Parallels between probabilistic and set vocabulary. Tribes. Probability.
Probabilityand independence
Conditional probability; total probability formula; Bayes formula. Independence of events; Poincaré formula.
Discreterandom variables.
Definition of a random variable. Law of probability. Distribution function. Moments. Random variable functions. Usual discrete laws: uniform, Bernoulli, binomial, hypergeometric, geometric, Poisson.
Density random variables:
Distribution function, density. Moments. Random variable functions. Laws defined by a usual density: uniform, exponential, normal law.
Necessary prerequisites
First-year analysis courses (HAX103X and HAX201X) and
HAX101X - Reasoning and Set Theory
HAX203X - Arithmetic and enumeration
Recommended prerequisites: L1 maths
Further information
Hourly volumes :
CM: 24
TD: 25.5
TP :
Terrain :