Course syllabus adopted 2021-02-26 by Head of Programme (or corresponding).
Overview
- Swedish nameSannolikhetsteorins grunder
- CodeMVE140
- Credits7.5 Credits
- OwnerMPENM
- Education cycleSecond-cycle
- Main field of studyMathematics
- DepartmentMATHEMATICAL SCIENCES
- GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Course round 1
- Teaching language English
- Application code 20145
- Open for exchange studentsYes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0107 Examination 7.5 c Grading: TH | 0 c | 7.5 c | 0 c | 0 c | 0 c | 0 c |
|
In programmes
- 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 Zuev- Full Professor, Analysis and Probability Theory, Mathematical Sciences
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.
The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.