Probability theory: probability, conditional probability, independenceone-dimensional random variablesbriefing about multi-dimensional random variablescommon distributionsmeasures (location, spreading and dependence) Law of Large Numbers, Central Limit Theorem Statistics: point estimates, confidence intervalshypothesis testregression analysis, correlation, graphical presentation of data.
IX1501 Mathematical Statistics 7.5 credits
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 TIDAB TIEDB programme students
- Course location
KTH Campus
- Duration
- 25 Aug 2025 - 24 Oct 2025
- Periods
- P1 (7.5 hp)
- Pace of study
50%
- Application code
50419
- Form of study
Normal Daytime
- Language of instruction
Swedish
- Course memo
- Course memo is not published
- Number of places
Min: 25
- Target group
Open to all programmes as long as it can be included in your programme.
- Planned modular schedule
- No information inserted
- Schedule
- Schedule is not published
Contact
Ki Won Sung (sungkw@kth.se)
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus IX1501 (Autumn 2021–)Content and learning outcomes
Course contents
Intended learning outcomes
General Objectives
After course completion the student should be able to:
- formulate, analyze and solve problems in statistics significant to in the ICT sphere.
- apply and develop statistical models with the aid of mathematical programming language.
- review and comment a given solution to a problem.
- comment domain and propose improvements to a statistical model.
- make presentations of solutions of a statistical problem.
Detailed Objectives
After course completion the student should be able to:
- apply basic stochastic models and use these to determine summary measures and probabilies.
- use normal approximation according to CLT.
- apply basic statistical models to an experiment.
- specify a standard model and comment the fitness for given data.
- describe data with summary measures, such as mean, variance and covariance.
- compute point estimates and confidence intervals.
- estimate error risks in hypothesis testing.
Literature and preparations
Specific prerequisites
- Knowledge in algebra and geometry, 7,5 credits, corresponding to completed course IX1303.
- Knowledge in calculus, 7,5 credits, corresponding to completed course IX1304.
Active participation in a course offering where the final examination is not yet reported in Ladok is considered equivalent to completion of the course.
Registering for a course is counted as active participation.
The term 'final examination' encompasses both the regular examination and the first re-examination.
Equipment
Literature
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- INLA - Assignment, 3.5 credits, grading scale: P, F
- TENA - Written exam, 4.0 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.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
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.
Further information
Course room in Canvas
Offered by
Main field of study
Education cycle
Add-on studies
Contact
Supplementary information
In this course, the EECS code of honor applies, see: http://www.kth.se/en/eecs/utbildning/hederskodex.