Study programme 2018-2019Français
Probability and Statistics I
Programme component of Bachelor's Degree in Mathematics à la Faculty of Science
CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-B2-SCMATH-009-MCompulsory UEGROSSE-ERDMANN KarlS844 - Probabilité et statistique
  • GROSSE-ERDMANN Karl

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français352000066.00Année

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-MATH-013Probability and Statistics I (Part A)1510000Q1
S-MATH-813Probability and Statistics I (Part B)2010000Q2
Programme component

Objectives of Programme's Learning Outcomes

  • Understand "elementary" mathematics profoundly
    • Understand one- and several-variable differential and integral calculus
    • Understand and use the naive set theory
    • Understand the fundamentals of probability and statistics
    • Manipulate previously acquired knowledge that appears in a question
    • Give examples and counterexamples for definitions, properties, theorems, etc.
  • Understand and produce strict mathematical reasoning
    • Write clearly and concisely
    • Use mathematical vocabulary and formalism appropriately
    • Make sense of formal expressions
    • Rely on a picture to illustrate a concept, rationale, etc.
  • Collaborate on mathematical subjects
    • Demonstrate independence and their ability to work in teams.
  • Solve new problems
    • Abstract and manipulate theories and use these to solve problems
    • Adapt an argument to a similar situation
    • Use knowledge from different fields to address issues
  • Address literature and interact within other scientific fields
    • Have sufficient knowledge of English in order to read and understand scientific texts, especially in the field of mathematics.

Learning Outcomes of UE

Basic notions of probability. Elements of measure and integration theory.

Content of UE

- Basic notions of probability - Introduction to measure theory - Introduction to integration theory - Random variables

Prior Experience

Good knowledge of naive set theory

Type of Assessment for UE in Q1

  • Written examination

Q1 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q2

  • Written examination

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

  • Oral examination

Q3 UE Assessment Comments

Not applicable

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-MATH-013
  • Cours magistraux
  • Exercices dirigés
S-MATH-813
  • Cours magistraux
  • Exercices dirigés

Mode of delivery

AAMode of delivery
S-MATH-013
  • Face to face
S-MATH-813
  • Face to face

Required Reading

AA
S-MATH-013
S-MATH-813

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-MATH-013Exercise sheets
S-MATH-813Not applicable

Recommended Reading

AA
S-MATH-013
S-MATH-813

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-MATH-013Not applicable
S-MATH-813Exercise sheets

Other Recommended Reading

AAOther Recommended Reading
S-MATH-013Jean Jacod, Philip Protter : L'essentiel en théorie des probabilités, Cassini
Dominique Foata, Aimé Fuchs : Calcul des probabilités, Dunod
S-MATH-813Jean Jacod, Philip Protter : L'essentiel en théorie des probabilités, Cassini
Dominique Foata, Aimé Fuchs : Calcul des probabilités, Dunod
(*) 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
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