- Probability spaces, random variables and their distributions, functions of random
variables, expectation - Independence, conditional probabilities, conditional expectation
- Probability and moment generating functions, characteristic function, sums of random variables
- Convergence of random variables, law of large numbers, central limit theorem
- Multivariate normal distribution and applications
SF2940 Probability Theory 7.5 credits

The overall purpose of the course is that the student should be well acquainted with basic concepts in probability theory, models and solution methods applied to real problems.
Information per course offering
Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.
Information for Autumn 2025 CINEK3 m.fl. programme students
- Course location
KTH Campus
- Duration
- 25 Aug 2025 - 24 Oct 2025
- Periods
- P1 (7.5 hp)
- Pace of study
50%
- Application code
50309
- Form of study
Normal Daytime
- Language of instruction
English
- Course memo
- Course memo is not published
- Number of places
Places are not limited
- Target group
- No information inserted
- Planned modular schedule
- [object Object]
- Schedule
- Schedule is not published
- Part of programme
Degree Programme in Engineering Mathematics, åk 3, Optional
Degree Programme in Engineering Physics, åk 3, Optional
Degree Programme in Industrial Engineering and Management, åk 3, TMAI, Mandatory
Master of Science in Engineering and in Education, åk 4, MAFY, Conditionally Elective
Master of Science in Engineering and in Education, åk 4, TEDA, Conditionally Elective
Master of Science in Engineering and in Education, åk 5, MAFY, Conditionally Elective
Master of Science in Engineering and in Education, åk 5, TEDA, Conditionally Elective
Master's Programme, Applied and Computational Mathematics, åk 1, Mandatory
Master's Programme, Biostatistics and Data Science, åk 1, Mandatory
Master's Programme, Computer Science, åk 1, CSTC, Conditionally Elective
Master's Programme, Computer Science, åk 2, CSCS, Recommended
Master's Programme, Computer Science, åk 2, CSDA, Recommended
Master's Programme, Computer Science, åk 2, CSTC, Conditionally Elective
Master's Programme, Machine Design, åk 1, Conditionally Elective
Master's Programme, Machine Learning, åk 1, Conditionally Elective
Master's Programme, Machine Learning, åk 2, Conditionally Elective
Master's Programme, Mathematics, åk 1, Optional
Master's Programme, Mathematics, åk 2, Optional
Master's Programme, Systems, Control and Robotics, åk 1, Recommended
Master's Programme, Systems, Control and Robotics, åk 2, Recommended
Contact
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus SF2940 (Spring 2023–)Content and learning outcomes
Course contents
Intended learning outcomes
The overall aim of the course is for students to become well-acquainted with basic probability theory concepts, models and solutions methods applied to concrete problem.
After passing the course, the students should be able to
- formulate and explain central definitions, results and theorems within probability theory
- systematically apply concepts and methods to independently solve basic problems within probability theory
- read and understand a mathematical text.
Literature and preparations
Specific prerequisites
- English B / English 6
- Completed basic coursein probability theory and statistic (SF1918, SF1922 or equivalent).
Recommended prerequisites
- Basic course in Multivariable Calculus (SF1626, SF1674 or equivalent)
- Basic course in Algebra and Geometry (SF1624 or equivalent)
Literature
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- TEN1 - Examination, 7.5 credits, grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.