• 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.

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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.

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Necessary prerequisites

First-year analysis courses (HAX103X and HAX201X) and  

HAX101X - Reasoning and Set Theory

HAX203X - Arithmetic and enumeration

 

Recommended prerequisites: L1 maths

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Further information

Hourly volumes :

            CM: 24

            TD: 25.5

            TP :

            Terrain :

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