Study programme 2018-2019Français
Probability and Statistics
Programme component of Bachelor's Degree in Engineering à la Faculty of Engineering
CodeTypeHead of UE Department’s
contact details
Teacher(s)
UI-B2-IRCIVI-003-MCompulsory UEGILLIS NicolasF151 - Mathématique et Recherche opérationnelle
  • DENDIEVEL Sarah
  • GILLIS Nicolas

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français242400044.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-MARO-005Probability1212000Q250.00%
I-MARO-007Statistics1212000Q250.00%
Programme component
Prérequis
Prérequis

Objectives of Programme's Learning Outcomes

  • Understand the theoretical and methodological fundamentals in science and engineering to solve problems involving these disciplines
    • Identify, describe and explain basic scientific and mathematical principles
    • Identify, describe and explain the basic principles of engineering particularly in their specialising field
    • Select and rigorously apply knowledge, tools and methods in sciences and engineering to solve problems involving these disciplines

Learning Outcomes of UE

- Understand and explain the basic concepts of probability and some important results (law of large numbers, Central Limit Theorem);- Solve simple applications implementing these concepts and results in a number of concrete situations (gambling, election polls, queues, fault diagnosis, ...); - Construct an interval containing almost certainly the value of a parameter of the distribution of a variable al- Testing the assumptions made on the value of parameters associated with random variables, and other assumptions such as independence, fit and homogénéit- Establish a linear regression model to an explanatory variable.

Content of UE

notions of probability: random variables and distribution; classical distributions; vectors al independence, correlation, normal distribution; laws of large numbers; central limit theorem, characteristic function, approximation to the binomial distribution by the normal distribution and the Poisson distribution; modeling real situations by probability (eg, queues, Google PageRank).

Notions of statistics: basic descriptive statistics in one and two dimensions (sample frequency, graphics); correlation; regression; independence; estimate average intervals, variance, proportion; regression coefficient; maximum likelihood method; hypothesis testing (population mean, proportion, variance, comparison of means and variances, fit, independence); linear regression model (in one variable).

Prior Experience

Calculus. 

Type of Assessment for UE in Q2

  • Written examination

Q2 UE Assessment Comments

50% probability, 50% statistics 

Type of Assessment for UE in Q3

  • Written examination

Q3 UE Assessment Comments

50% probability, 50% statistics 

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-MARO-005
  • Cours magistraux
  • Conférences
  • Exercices dirigés
  • Démonstrations
I-MARO-007
  • Cours magistraux
  • Conférences
  • Exercices dirigés
  • Démonstrations

Mode of delivery

AAMode of delivery
I-MARO-005
  • Face to face
I-MARO-007
  • Face to face

Required Reading

AARequired Reading
I-MARO-005Note de cours - Note de cours de Probabilités - Nicolas Gillis et Marc Pirlot
I-MARO-007Note de cours - Statistiques - Nicolas Gillis et Marc Pirlot

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-MARO-005Not applicable
I-MARO-007Not applicable

Recommended Reading

AARecommended Reading
I-MARO-005Notes d'exercices - Exercices - Jacques Teghem
I-MARO-007

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-MARO-005Sans objet
I-MARO-007Sans objet

Other Recommended Reading

AAOther Recommended Reading
I-MARO-005Not applicable
I-MARO-007Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-MARO-005Authorized
I-MARO-007Authorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 02/05/2019
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be