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Syllabus for

Academic year
MVE155 - Statistical inference
 
Syllabus adopted 2013-02-21 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English
Open for exchange students
Block schedule: LA

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5c Grading: TH   7,5c   11 Mar 2014 pm V,  09 Jun 2014 am V,  29 Aug 2014 pm V

In programs

MPBME BIOMEDICAL ENGINEERING, MSC PROGR, Year 1 (compulsory elective)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (compulsory)
TKITE SOFTWARE ENGINEERING, Year 3 (compulsory elective)

Examiner:

Professor  Serik Sagitov


Course evaluation:

http://document.chalmers.se/doc/14076d8f-71bf-4733-8fcf-cc07d78d9a36


  Go to Course Homepage

Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

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

Written examination.
Bonus points for an optional laboratory assignment.


Published: Mon 28 Nov 2016.