Home

Education

Postgraduate course

Ordination and Gradient Analysis

  • ECTS credits5
  • Teaching semesterAutumn
  • Course codeBIO303
  • Number of semesters1
  • LanguageEnglish
  • Resources

Teaching semester

Autumn.

The registration deadline for enrollment in the course is Thursday in week 33 for the autumn semester. You will receive confirmation of whether you received a spot in Studentweb no later than Tuesday the week after the deadline.

The time of the first lecture/orientation meeting can be found in the schedule on the course website or on the Mitt UiB learning platform.

Objectives and Content

The course introduces some statistical tools for analysing and interpreting ecological data. It consists of lectures and computer based practicals covering direct and indirect ordination, cluster analysis and regression trees. The course is followed by a take home exam which covers both theoretical and practical aspects of the course.

Learning Outcomes

 After completing the course, students should be able to:

  • Explain why the statistical properties of ecological data mean it can needs appropriate methods
  • Explain why parsimonious models and methods should be preferred
  • Describe the advantages and disadvantages of different numerical methods
  • Choose appropriate techniques for analysing data
  • Interpret diagnostics
  • Build parsimonious models
  • Generate and interpret relevant plots
  • Analyses data in a modern statistical package

Have some of the statistical skills necessary for their thesis projects

Required Previous Knowledge

Bachelor degree in Biology

Forms of Assessment

Home exam

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Course Evaluation

Students will evaluate the course in accordance with the quality assurance system at UiB and the Department. You can find courseevaluations in the Quality Assurance Reports.

Contact

Contact Information

Contact the Study Section at the Department of Biological Sciences: studie@bio.uib.no