NBID31 · 6 credits · Advanced level (A1N) · Biologi
Modelling of Biological Systems
Discontinued · replaced by NBID85
100%
passed the latest regular sitting
UPG3 · 16 Jan 2026 · 23 students
100%
passed the regular sittings, all sittings over the last 5 years
UPG3 · 113 students
This module only reports passing results, so the pass rate does not show how many did not pass.
Part of 2 programmes
Hand-in or lab
UPG3 Assignments
- G
Main rounds
100% passed · 113 students
- 100%23
- 100%37
- 100%30
- 100%23
Later rounds
100% passed · 10 students
- 100%10
- Pass a later round: 100% (10 students), compared with 100% (113 students) on the ordinary exam
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
UPG4 Modeling project
- G
Main rounds
100% passed · 105 students
- 100%22
- 100%37
- 100%29
- 100%17
Later rounds
100% passed · 15 students
- 100%5
- 100%10
- Pass a later round: 100% (15 students), compared with 100% (105 students) on the ordinary exam
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
- 100%1
- 100%1
- 100%1
- 100%1
Hand-in or lab
UPG1 Assignments
- G
No sittings with at least 5 students.
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
About the course
Aim
The aim is that students should be able to acquire and utilize basic knowledge of mathematical and statistical models for applied and theoretical problems in ecology and biology, as well as to be able to construct and use models in the program language R. Students shall be able to handle the four stages after completion of the course:
- Formulate and construct a mathematical model from verbal description of known experimental relations
- Mathematically analyze and apply a model
- Interpret and evaluate the mathematical analysis in the context of the experimental knowledge
- Present the model and its results.
Upon completion of the course the student is expected to complete the basic programming tasks and visualization tasks in R.
Content
Basic programming in R such as; familiarity with standard functions found in R, create their own functions in R, use of R for large data analysis, as well as visualization of data in R.
The models that will be treated are; models in discrete and continuous time, deterministic and stochastic models.
Presentation skills.
- Examiner
- Anna Eklöf
- Scheduled hours
- 48 h
- Main field of study
- Biologi