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Syllabus for

Academic year
TMS150 - Stochastic data processing and simulation
Statistisk databehandling
 
Syllabus adopted 2019-02-22 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English
Application code: 20142
Open for exchange students: Yes

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0103 Project 7,5c Grading: TH   7,5c    

In programs

MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory elective)
TKTEM ENGINEERING MATHEMATICS, Year 2 (compulsory)

Examiner:

Umberto Picchini

  Go to Course Homepage


Eligibility

General entry requirements for Master's level (second 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

English 6 (or by other approved means with the equivalent proficiency level)
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

A basic course in mathematical statistics. Some programming experience is recommended - contact the examiner if in doubt about this.

Aim

The main goal of the course is to introduce the student to some important mathematical and statistical programming languages, via work on concrete mathematical and mathematical statistical problems.

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

  • be able to use these programming languages as natural tools in later courses;
  • have developed problem solving skills;
  • be able to move between analytical and numerical problem solving methods with
    the use of a computer;
  • be able to write mathematical reports using LaTeX.

Content

The core of the course are several projects in different areas of mathematical statistics and its applications (e.g., finance, bioinformatics).  Each project contains a number of problems to be solved in a given programming language, e.g., Matlab, Python, and R.  The projects are presented at lectures and programming languages are introduced during teacher led laboratories. The project reports are to be written in LaTeX.

Organisation

Lectures that introduce the projects. Demonstrations of computer programs. Supervision of projects.

Literature

Mainly handouts. But see the course homepage before the course starts.

Examination including compulsory elements

Written reports of the results of the work with the projects. The grading is based on how the problems in the projects are solved and reported.


Published: Mon 28 Nov 2016.