Course syllabus for Mathematical statistics

The course syllabus contains changes
See changes

Course syllabus adopted 2019-02-19 by Head of Programme (or corresponding).

Overview

  • Swedish nameMatematisk statistik
  • CodeTMA074
  • Credits7.5 Credits
  • OwnerTKKMT
  • 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 53116
  • Maximum participants60
  • Open for exchange studentsNo
  • Only students with the course round in the programme overview.

Credit distribution

0115 Project 1.5 c
Grading: UG		1.5 c
0215 Examination 6 c
Grading: TH		6 c
  • 28 Okt 2020 pm J
  • 04 Jan 2021 pm J
  • 16 Aug 2021 am 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

Analysis and linear algebra.

Aim

The course will cover the basics of probability theory and statistics that are important for chemists.

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

After passing the course the student should understand the basic conceptions in probability theory and statistical inference. The course should also give the students the ability to plan statistical experiments and perform simple statistical analyses.

Content

Descriptive statistics, sample space, probability, conditioning, measures of central tendency and dispersion. Discrete and continuous distributions, and modelling using various standard distributions such as the binomial and normal distributions. Methods to compute with stochastic variables, some rules to compute expected values and variances. The central limit theorem, multivariate distributions, and covariance. Parameter estimation, confidence intervals, and tests in different standard situations. Introduction to linear regression and design of experiments.

Organisation

Lectures, exercise sessions, computer exercises, and one project.

Literature

Milton, J.S & Arnold, J.C: Introduction to Probability and Statistics
Zetterqvist, L. & Lindström, J.: Räkna med variation

Examination including compulsory elements

Written exam and a project.

The course syllabus contains changes

  • Changes to examination:
    • 2020-09-30: Grade raising No longer grade raising by GRULG
  • Changes to course rounds:
    • 2020-05-29: Examinator Examinator changed from Moritz Schauer (smoritz) to Erik Kristiansson (erikkr) by Viceprefekt
      [Course round 1]