Non-parametric analyses applied to social dimensions data of forest research
Course description
Researchers often have to analyse information that comes in a quantifiable but non-scalar form, or that may violate assumptions of a normal distribution that prevent commonly-used parametric inferences.
This course reviews and discusses the opportunities and limitations of using non-parametric methods to analyse ordinal, categorical and non-normally distributed data. Specific non-parametric tests will be discussed with active doctoral student engagement. Expectations include in-course active participation, an oral presentation and a report where non-parametric analyses are used and their findings interpreted.
Course facts
P000196, Non-parametric analyses applied to social dimensions data of forest research, 3.0 Hp
Print syllabus
Syllabus
Finalized by: Magnus Rudolfsson, 2026-10-22
Valid from :
Level
Third cycle
Subject
Applied economics
Grading Scale
One-grade scale
The grade requirements within the course grading system are set out in specific criteria. These criteria must be available by the course start at the latest.
Course language
English
Entry Requirements
Objectives
On completion of the course, the student will be able to:
- *Describe research question**s *and data when non-parametric analyses are preferred to parametric options
- Enumerate select examples of tests suitable for non-parametric analyses
- Interpret and critically evaluate results and draw reasonable conclusions
- Clearly and concisely communicate results and conclusions.
Content
The course is carried out with lectures, student-centred analyses and presentations. The course provides an introduction to non-parametric data and analyses, with a motivation for situations where data may exist in quantifiable but non-scalar form, or that may violate assumptions of a normal distribution that prevent parametric inferences. Specific tests (e.g., Mann-Whitney, Wilcoxon signed-rank, Kruskal-Wallis test) will be discussed for their correct application. Doctoral level knowledge on the use of specific non-parametric statistics and their interpretation is gained via engaged discussions, and their applications with specific data and interpretation of findings. Sustainable development and gender equality perspectives are discussed via reflections regarding findings and how results can inform actions towards improved sustainable and equality conditions. Students are encouraged to bring their own data but the instructor will provide datasets if needed.
Examination Formats and Requirements for Passing the Course
*Approved written report and oral presentation. *
Responsible Department/Equivalent
Department of forest bioeconomy and technology
Supplementary information
Other Information
This course is jointly organized by the Faculty of Forest Sciences