ECTS
5 credits
Component
Faculty of Science
Description
This course will introduce probability spaces, the notions of probability and independence and will define discrete and density random variables with an emphasis on modeling.
Objectives
Probabilized spaces.
Randomized experiments. Events. Parallel between probabilistic and set vocabulary. Tribes. Probability.
Probabilityconditional probability and independence
Conditional probability; total probability formula; Bayes' formula. Independence of events; Poincaré's formula.
Discreterandom variables.
Definition of a random variable. Law of probability. Distribution function. Moments. Functions of a random variable. Usual discrete laws: uniform, Bernoulli, binomial, hypergeometric, geometric, Poisson.
Random variables with density:
Distribution function, density. Moments. Functions of random variables. Laws defined by a usual density: uniform, exponential, normal law.
Necessary pre-requisites
The first year analysis courses (HAX103X and HAX201X) and
HAX101X - Reasoning and Set Theory
HAX203X - Arithmetic and Enumeration
Recommended prerequisites: L1 math
Additional information
Hourly volumes:
CM : 24
TD : 25,5
TP:
Terrain: