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Informatique et Mathématiques appliquées
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> Formation > Cursus ingénieur

Probability - 3MM1PA

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  • Number of hours

    • Lectures : 18.0
    • Tutorials : 18.0
    • Laboratory works : -
    • Projects : -
    • Internship : -
    • Written tests : -
    ECTS : 3.0
  • Officials : Herve GUIOL

Goals

Learn the language and basic concepts of probability.
Provide tools for modeling randomness.
Use of a simulation and statistical software: R.
This course will serve as a basis for the study of systems involving random phenomena encountered in most fields of engineering.
This is a prerequisite for courses like Probability for Computer Science and Principles and Meythods for Statistics.

Content

Use and counting of sets: applications to game's theory.
Conditional probabilities, Bayes formula, Base rate fallacy.
Random variables, distributions, mean, variance and standart deviation.
Usual distributions : Bernoulli, Binomial, Geometric, Poisson, Uniform, Exponential, Gamma, Normal
Joined distibutions, Covariance, Correlation and Independence.
Simulation: by inversion, rejection method, law of large numbers, Monte Carlo method

    • This lecture is scheduled in "Période(s) Académique(s) 1 and 3" **

Prerequisites

Basic notions in mathematics.

Tests

Two partial examinations (E1 & E2).
Continuous assesment : CC

  1. Lexique et formules
    E1 : Examen de période 1
    E2 : Examen de période 3
    CC : contrôle continu
    N1 = (maximum(E2;(E2+E1)/2)+CC)/2 # moyenne des périodes 1 et 3 et contrôle continu
    N2 = (O+CC)/2 # note de rattrapage, la partie du contrôle continu n'est pas rattrapable

# Calcul de la note de chaque période remontée à la scolarité:
NP1 = E1
NP3 = N1

# Calcul des notes des deux bilans:
NB1 = NP1
NB2 = NB1

# Calcul des notes pour les jurys session 1 et 2
NFS1 = NP3
NR = N2
NFS2 = NR

Calendar

The course exists in the following branches:

  • Curriculum - Work Study Education - Alternance 1ere annee
see the course schedule for 2020-2021

Additional Information

Course ID : 3MM1PA
Course language(s): FR

The course is attached to the following structures:

You can find this course among all other courses.

Bibliography

Introduction to Probability and Statistics, MIT Open Courseware
G. Grimmett, Probability Theory and Examples. Oxford.

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Date of update January 15, 2017

Université Grenoble Alpes