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Course content

This course provides an introduction to distribution modelling and data processing and analytical tools used in this field. Through lectures and practical exercises the course gives an introduction to the theory of distribution modeling, overview of data, methodology, software and useful distribution modelling tools, and evaluation of strengths, weaknesses, errors and uncertainties throughout the distribution modelling process. The students shall write a mandatory project report and discuss the subject during a mandatory plenary session.

Learning outcome

The course will provide a sound theoretical understanding of the principles of distribution modelling and practical experience with some of the most important data analysis tools used in this field. Through the project report and the practical distribution modelling work and the accompanying project discussion, participants will gain the ability to critically evaluate the whole process of distribution modelling.

Students attending BIOS9211 will have a significantly larger syllabus compared to students at BIOS5211, and are expected to develop a deeper understanding of distribution modelling both in terms of theoretical basis and practical applications.

Admission to the course

PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.

If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.

PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.

The courses BIOS5211 and BIOS9211 have common admission. Applicants are ranked by the following criteria:

  1. PhD students and master students at the MN faculty who have the course as part of the approved curriculum.
  2. Other PhD students and visiting PhD students.
  3. Students with admission to single courses on master’s level and exchange students

Applicants are ranked by credits in each group; all applicants within 1st rank before applicants in 2nd etc. If admission is limited to a fixed number of participants, admission will be decided by drawing lots for students who are ranked equally

BIOS1150 – Biodiversity, BIOS2100 – General Ecology, STK1000 – Introduction to Applied Statistics og BIOS5210 – Methods of Gradient Analysis.

The course does not provide technical training in geographical information systems (GIS). Knowledge of GIS and statistical software (R) will be an advantage.

Overlapping courses


  • Lectures
  • Computer laboratory/ practical data laboratory exercises
  • A mandatory project report providing the basis for the presentation and discussion at a mandatory final plenary presentation lasting 1-2 days

 Attendance for all lectures and data laboratory exercises is required; although, a 20% absence for special circumstances is permitted. Attendance to the final plenary sessions is mandatory and non-negotiable.

Attendance is mandatory for the first lecture. This also applies for those on the waiting list. You will lose your seat on the course if documentation for absence is not provided to the student administration prior to the first lecture.

The course will be given during week 46-50 (November and December). Lectures and data laboratory exercises will be given in a concentrated block in the first half. The mandatory project report must be submitted and will be evaluated (approved/not approved) before the plenary session. Approved project reports will be made available to all participants, presented and discussed on the final plenary sessions in December.

Students attending BIOS9211 will have to read approx. 10 scientific papers with relevant literature. Compared to students at BIOS5211, they have to discuss more issues in their project report and during the practical modelling tasks.


To pass the course you have to:

  • Get approved mandatory participation on the lectures and the data laboratory exercises
  • Get approved the mandatory project report
  • Get approved mandatory presentation and discussion at the final plenary session

Students attending BIOS9211 are assumed show a deeper understanding of distribution modelling both in terms of theoretical basis and practical applications than students at BIOS5211.

Exam attempts

It will also be counted as one of the three attempts to sit the exam for this course, if you sit the exam for one of the following courses: BIOS5211 – Distribution Modelling, BIO4115 – Distribution modelling (continued) and BIO9115 – Distribution modelling (continued).

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Resit an examination

This course offers both postponed and resit of examination. Read more:

Special examination arrangements, use of sources, explanations and appeals

See more about examinations at UiO

Last updated from FS (Common Student System) Aug. 16, 2022 6:21:06 PM

Facts about this course

Teaching language
Norwegian (English on request)