Non-parametric Methods

7.5 credits

Syllabus, Master's level, 1MS020

This course has been discontinued.

A revised version of the syllabus is available.

Code: 1MS020
Education cycle: Second cycle
Main field(s) of study and in-depth level: Mathematics A1N
Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by: The Faculty Board of Science and Technology, 6 November 2007
Responsible department: Department of Mathematics

Entry requirements

120 credit points and Analysis of Regression and Variance

In order to pass the course (grade 3) the student should be able to

give an account of the most common non-parametric methods for analysis of data;

apply the most common non-parametric methods in practice, in particular in medical applications;

decide when a non-parametric method is more suitable than a parametric method;

use statistical software in order to perform permutation tests and bootstrap on data sets.

Sign tests. Rank-sum tests. Non-parametric confidence intervals. Correlation and regression analysis. One-way and two-way comparison. Bootstrap.

Lectures, problem solving sessions and computer-assisted laboratory work.

Written examination at the end of the course. Compulsory assignments and laboratory work during the course.