Non-parametric Methods
Syllabus, Master's level, 1MS020
This course has been discontinued.
- 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, 30 August 2018
- Responsible department
- Department of Mathematics
Entry requirements
120 credits including Analysis of Regression and Variance. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Learning outcomes
On completion of the course, 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.
Content
Sign tests. Rank-sum tests. Non-parametric confidence intervals. Correlation and regression analysis. One-way and two-way comparison. Bootstrap.
Instruction
Lectures, problem solving sessions and computer-assisted laboratory work.
Assessment
Written examination at the end of the course. Compulsory assignments and laboratory work during the course.
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.