Course syllabus for Mathematical statistics and discrete mathematics

The course syllabus contains changes
See changes

Course syllabus adopted 2024-01-28 by Head of Programme (or corresponding).

Overview

  • Swedish nameMatematisk statistik och diskret matematik
  • CodeMVE055
  • Credits7.5 Credits
  • OwnerTKDAT
  • 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 English
  • Application code 49125
  • Open for exchange studentsNo
  • Only students with the course round in the programme overview.

Credit distribution

0105 Examination 6 c
Grading: TH		6 c
  • 29 Okt 2024 pm J
  • 07 Jan 2025 pm J
  • 27 Aug 2025 pm J
0205 Written and oral assignments 1.5 c
Grading: UG		1.5 c

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 knowledge of discrete mathematics, linear algebra and calculus.

Aim

The aim of the course is to give
  • understanding of basic knowledge in probability theory, statistics, and combinatorics which is impotrant for technical studies and specifically for studies in information technology
  • skills for understanding ang using mathematical language
  • ability to communicate mathematics

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

  • identify problems arising in technical studies and specifically in information technology for which the treatment requires use of fundamental concepts and methods from Probability theory and Mathematical statistics.
  • describe and analyze such problems in terms of statistics and discrete mathematics.
  • be familiar with fundamental notions and problems in data analysis, including casuality and hidden variables, and how these arise in real examples, where diversity, equity, and inclusion (DEI) is one of several central examples.
  • apply basic statistical methods such as parameter and interval estimation, testing of statistical hypotheses, and linear regression, in problem solving.

Content

The course covers topics in a number of areas. Within each area relevant mathematical concepts are studied. These concepts are considered on different levels of depth. The topics discussed are:
  • Probability theory and Markov chains: random variables, expectation, variance, correlation, conditional probability, the law of large numbers, the central limit theorem.
  • Statistics: point estimation, confidence intervals, hypotheses testing.
  • Combinatorics: combinations, permutations, generating functions.
In probability theory, the emphasis is on discrete models.

Organisation

Main course activities:
  • Lectures which elucidate and explain the mathematical theory.
  • Exercise sessions where related problems are solved individually or in groups.

Literature

Will be announced later.

Examination including compulsory elements

Written examination. Compulsory turn in assignments.

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.

The course syllabus contains changes

  • Changes to course rounds:
    • 2024-05-02: Examinator Examinator changed from Moritz Schauer (smoritz) to Christian Johansson (chrjohv) by Viceprefekt/adm
      [Course round 1]