Course syllabus for Statistics with applications

Course syllabus adopted 2020-02-27 by Head of Programme (or corresponding).

Overview

  • Swedish nameTillämpad matematisk statistik
  • CodeLMA522
  • Credits7.5 Credits
  • OwnerTIMAL
  • Education cycleFirst-cycle
  • Main field of studyMathematics
  • DepartmentMATHEMATICAL SCIENCES
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language Swedish
  • Application code 65138
  • Open for exchange studentsNo
  • Only students with the course round in the programme overview.

Credit distribution

0118 Examination 7.5 c
Grading: TH		 7.5 c
  • 15 Mar 2021 am L
  • 08 Jun 2021 pm L
  • 26 Aug 2021 pm L

In programmes

Examiner

Go to coursepage (Opens in new tab)

Eligibility

General entry requirements for bachelor's level (first 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

The same as for the programme that owns the course.
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 courses LMA401 Calculus and MVE580 Linear algebra and differential equations, or corresponding knowledge.

Aim

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.

Content

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.

Organisation

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

Literature

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 (grade 3) the student needs to get at least 20p. 30p is required for grade 4 and 40p for grade 5.