Course syllabus adopted 2024-02-05 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 20140
- Open for exchange studentsYes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0107 Examination 7.5 c Grading: TH | 7.5 c |
In programmes
- MPCAS - COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory elective)
- MPENM - ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory)
- MPMED - BIOMEDICAL ENGINEERING, MSC PROGR, Year 1 (elective)
- TKITE - SOFTWARE ENGINEERING, Year 3 (elective)
Examiner
Aila Särkkä- 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
- parametric and non-parametric inference
- analysis of variance, linear least squares, chi-squared tests for categorical data
- elements of Bayesian inference.
Organisation
Lectures and exercises.
Literature
Compendium "Statistical inference" by Serik Sagitov.
Lecture notes downloadable from the course homepage.
Mathematical statistics and data analysis by John A. Rice.
Examination including compulsory elements
Written examination. Optional assignments that can give bonus points on the exam may occur.
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.