Number of hours
- Lectures 18.0
- Projects -
- Tutorials 18.0
- Internship -
- Laboratory works -
- Written tests -
ECTS
ECTS 3.0
Goal(s)
Learn the language and basic concepts of probability.
Provide tools for modeling randomness for engineering.
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 computer engineering.
Responsible(s)
Herve GUIOL
Content(s)
Conditional probabilities, Bayes formula, Base rate fallacy.
Random variables, distributions, mean.
Usual distributions : Bernoulli, Binomial, Geometric, Poisson, Uniform, Exponential, Gamma, Normal
Independence of random variables.
Markov chain, Poisson processes and Queing theory.
- This lecture is scheduled in "Période(s) Académique(s) 1 and 3" **
Basic notions in mathematics.
Test
Evaluation : 30% of Participation et assiduité and 70% of Rapport écrit et soutenance (2h)
Resit : Examen oral (exposé, soutenance, etc..) (20 min)
Two partial examinations (E1 & E2).
Continuous assesment : CC
Calendar
The course exists in the following branches:
- Curriculum - Work Study Education - Alternance 1ere annee
Additional Information
Course ID : 3MM1PA
Course language(s): 
The course is attached to the following structures:
- Team Probability-Statistics
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.