Search programme

​Use the search function to search amongst programmes at Chalmers. The study programme and the study programme syllabus relating to your studies are generally from the academic year you began your studies.

Syllabus for

Academic year
MVE140 - Foundations of probability theory
Sannolikhetsteorins grunder
 
Syllabus adopted 2019-02-22 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English
Application code: 20130
Open for exchange students: Yes

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5c Grading: TH   7,5c   16 Jan 2021 am J  

In programs

MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory elective)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 2 (elective)

Examiner:

Sergey Zuyev

  Go to Course Homepage


Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

The student is supposed to have completed a course comprising a substantial part of basic probability theory.

Aim

To provide the students experiences of the strength of probability theory and its applications.

Learning outcomes (after completion of the course the student should be able to)

- identify and properly formulate probabilistic models for real-life phenomena

- explain the foundations of probability and its relations to measure theory, set theory and Lebesgue integration

- explain and motivate the main probability distributions, their properties and range of applications

- use dependence and
conditioning in complex situations

carry out analytical probability calculations, including use of transforms.

Content

Probability experiment, events, random variables and their distributions,  independence and conditional distributions, random vectors and sequences, convergence, the strong law of large numbers, transforms and the central limit theorem.

Organisation

The course comprises lectures, and tutorials with exercises and discussions.

Literature

See the course homepage http://www.math.chalmers.se/Stat/Grundutb/CTH/mve140

Examination including compulsory elements

The assessment is mainly based on a written final examination. Bonus points can also be obtained for presentation of home assignments at the tutorials.


Published: Mon 28 Nov 2016.