Course syllabus adopted 2021-02-26 by Head of Programme (or corresponding).
Overview
- Swedish nameStatistisk slutledning
- CodeMVE155
- Credits7.5 Credits
- OwnerMPENM
- Education cycleSecond-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 20131
- Open for exchange studentsYes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0107 Examination 7.5 c Grading: TH | 0 c | 0 c | 7.5 c | 0 c | 0 c | 0 c |
|
In programmes
- MPBME - BIOMEDICAL ENGINEERING, MSC PROGR, Year 1 (compulsory elective)
- MPCAS - COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory elective)
- MPENM - ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory)
- TKITE - SOFTWARE ENGINEERING, Year 3 (elective)
Examiner
Serik Sagitov- Full Professor, Applied Mathematics and Statistics, Mathematical Sciences
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 first course in probability and statistics worth of 7.5 credits.
Aim
To give the students insight in tecniques for treating multiple sample data, sampling designs, and appropriate statistical tests for this kind of data
Learning outcomes (after completion of the course the student should be able to)
- summarize multiple sample data in a meaningful and informative way,
- recognize several basic types of statistical problems corresponding to various sampling designs,
- estimate relevant parameters and perform appropriate statistical tests for multiple sample data sets.
Content
This is a second course in mathematical statistics introducing the following key topics of statistical inference:
- sampling designs and summarizing data
- maximum likelihood estimation of parameters, bootstrap
- parametric and non-parametric inference
- the analysis of variance, linear least squares, categorical data
- elements of Bayesian inference.
Organisation
Lectures, exercises, and optional computer assignments.
Literature
Mathematical statistics and data analysis by John A. Rice. Lecture notes downloadable from the internet.
Examination including compulsory elements
Written examination.
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 examination:
- 2022-04-23: Exam date Exam date changed by Elisabeth Eriksson
[34534, 56618, 3], New exam for academic_year 2021/2022, ordinal 3 (not discontinued course) - 2022-01-17: Exam date Exam date changed by Elisabeth Eriksson
[34534, 56618, 2], New exam for academic_year 2021/2022, ordinal 2 (not discontinued course)
- 2022-04-23: Exam date Exam date changed by Elisabeth Eriksson