Course syllabus for Mathematical statistics

The course syllabus contains changes
See changes

Course syllabus adopted 2019-02-14 by Head of Programme (or corresponding).

Overview

  • Swedish nameMatematisk statistik
  • CodeTMA321
  • Credits4.5 Credits
  • OwnerTKTFY
  • Education cycleFirst-cycle
  • Main field of studyMathematics, Engineering Physics
  • DepartmentMATHEMATICAL SCIENCES
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language Swedish
  • Application code 57139
  • Maximum participants130
  • Open for exchange studentsNo
  • Only students with the course round in the programme overview.

Credit distribution

0194 Examination 4.5 c
Grading: TH		 4.5 c
  • 02 Jun 2021 am J
  • 10 Okt 2020 pm J
  • 17 Aug 2021 pm J

In programmes

Examiner

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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

Basic courses in one variable and multivariable analysis, and linear algebra. Some knowledge of MATLAB.

Aim

Our aim is to give a new view of measurement and information focusing on the variation and uncertainty and on efficient mathematical tools to handle randomness and uncertainty. The usefulness of this approach will be illustrated by physical, technical and other examples.

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

  • Conduct calculations using probabilistic tools and formalism
  • Be aware of, be able to use and explain common terminology within the area of mathematical statistics
  • Perform statistical modeling of simple situations
  • Plan data collection for simple statistical trials
  • Perform a statistical analysis of data from simple trials
  • Interpret the result of statistical trials performed by others

Content

Sample space, probability and conditioning. Modelling with different probability distributions. Computations involving random variables, expected values and variances. The Central limit theorem and approximation of distribution. Parameter estimation methods, ML-estimation, confidence intervals and hypothesis testting in different standard situations. Random vectors and introduction to regression. Some models in physics eg radioactivity (Poisson processes etc.) will be briefly overviewed.

Organisation

Lectures and problem solving exercises as sheduled. Two home assignments partly involving simulations. 

Examination including compulsory elements

A written exam.

The course syllabus contains changes

  • Changes to course rounds:
    • 2021-02-08: Examinator Examinator changed from Erik Broman (broman) to Johan Jonasson (jonasson) by Viceprefekt
      [Course round 1]
  • Changes to course:
    • 2020-10-09: Litterature Litterature changed by Viceprefekt
      Removed information about litterature