Course syllabus adopted 2021-02-26 by Head of Programme (or corresponding).
Overview
- Swedish nameMatematisk statistik
- CodeMVE495
- Credits3 Credits
- OwnerTKSAM
- 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 58126
- Open for exchange studentsNo
- Only students with the course round in the programme overview.
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0116 Written and oral assignments 3 c Grading: TH | 3 c |
In programmes
- TISAM - CIVIL AND ENVIRONMENTAL ENGINEERING, Year 2 (compulsory)
- TKSAM - CIVIL ENGINEERING, Year 2 (compulsory)
Examiner
Sergey Zuev- Full Professor, Analysis and Probability Theory, Mathematical Sciences
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.
Aim
The aim of the course is give the students basic techniques to analyze and present data and account for variability.Learning outcomes (after completion of the course the student should be able to)
After course completion, the student should be able to:- present the data giving graphical and numeric summaries
- analyse the main probability models
- analyze and quantify dependence between measurements
- apply such methods in practice
Content
The course covers the following topics: - samples, their graphical presentation and numeric summaries - basics of probability, random variables and their characteristics - point and interval estimates of the sample distributional characteristics - bivariate data: correlation and regressionOrganisation
The teaching is organised around a web-based Virtual Learning Environment (VLE) and a statistical project complemented by consultations and assisted computer labs. Students will learn to master statistical computation on Matlab package. It's previous knowledge would be a big helper.Literature
The manual linked in the VLE provides the necessary and sufficient source of information. As an additional reading, the following book is recommended:Douglas C. Montgomery and George C. Runger. Applied Statistics and Probability for Engineers, Wiley, 2007.
Examination including compulsory elements
Examination will be held within the VLE with a similar to the usual working VLE interface and consists of the same kind of questions as in the practice.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.