BIOS5211 – Distribution Modelling
Schedule, syllabus and examination date
Changes in the course due to coronavirus
Autumn 2020 we plan for teaching and examinations to be conducted as described in the course description and on semester pages. However, changes may occur due to the corona situation. You will receive notifications about any changes at the semester page and/or in Canvas.
Spring 2020: Teaching and examinations was digitilized. See changes and common guidelines for exams at the MN faculty spring 2020.
This course provides an introduction to distribution modelling and to essential 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, critical evaluation of strengths, weaknesses, errors and uncertainties throughout the distribution modelling process, overview of data, methodology, software and useful tools, preparation for analyses and practical modelling exercises. The students shall write a mandatory project report and discuss the subject during a mandatory plenary session.
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 discussion, participants will gain the ability to critically evaluate the whole process of distribution modelling.
Admission to the course
Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.
PhD-students have to register to BIOS9211 – Distribution Modelling.
The courses BIOS5211 and BIOS9211 have common admission. Applicants are ranked by the following criteria:
- PhD students and master students at the MN faculty who have the course as part of the approved curriculum.
- Other PhD students and visiting PhD students.
- 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
Recommended previous knowledge
The course does not provide technical training in geographical information systems (GIS). Knowledge of GIS and statistical software (R) will be an advantage.
- 10 credits overlap with BIOS9211 – Distribution Modelling.
- 10 credits overlap with BIO4115 – Distribution modelling (continued).
- 10 credits overlap with BIO9115 – Distribution modelling (continued).
- 5 credits overlap with BIO4110 – Ecological GIS modelling (discontinued).
- 5 credits overlap with BIO9110 – Ecological GIS modelling (discontinued).
- 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 session 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 email@example.com 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.
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
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: BIOS9211 – Distribution Modelling, BIO4115 – Distribution modelling (continued) and BIO9115 – Distribution modelling (continued).
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: