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Use the search function to find more information about the study programmes and courses available at Chalmers. When there is a course homepage, a house symbol is shown that leads to this page.

Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
LMA521 - Statistics with applications  
Tillämpad matematisk statistik
Syllabus adopted 2019-02-14 by Head of Programme (or corresponding)
Owner: TIEPL
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: First-cycle
Major subject: Mathematics

Teaching language: Swedish
Application code: 68129
Open for exchange students: No

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0103 Examination 7,5 c Grading: TH   7,5 c   14 Jan 2020 am L,  02 May 2020 pm DIST   27 Aug 2020 am L

In programs

TIDSL PRODUCT DESIGN ENGINEERING, Year 3 (compulsory elective)
TIDAL COMPUTER ENGINEERING, Year 3 (compulsory elective)


Johan Tykesson

  Go to Course Homepage


In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.

Course specific prerequisites

Courses in Calculus and Linear Algebra


The course intends to give the students knowledge in basic probability theory and statistical inference. This knowledge is essential for the understanding of the statistical methods and tests used in technical and natural sciences.

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

- understand how different situations are influenced by chance,
- calculate risks,
- draw conclusions from surveys,
- plan experiments using factorial and fractional factorial designs,
- apply control charts; to construct them and draw conclusions about the examined process,
- decide if a production process produces articles that will meet the customer s demand.


Descriptive statistics, elementary probability, dependent and independent events, discrete and continuous distributions, expectation, variance, the central limit theorem (without proof), interval estimation. Experimental designs, factorial designs, fractional factorial designs, blocking, randomisation. Statistical quality control, control charts, acceptance sampling procedures.


The course consists of 35 lectures in which exercises are included and one obligatory laboratory work.


See the course web page

Examination including compulsory elements

To pass the course the student must pass both a thesis and one laboratory work. The maximum point on the thesis is always 50. To pass the thesis one needs to get at least 20p. To get class 3 the student needs at least 20 p, for class 4 30 p and for class 5 40p.

Page manager Published: Thu 04 Feb 2021.