The course provides a practical introduction to reproducible data handling, data visualisation, and statistical modeling using the programming software R. With a focus on univariate models, the course provides knowledge about when and how to apply different statistical models depending on the type of design and type of data.
Learning Outcomes
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The candidate ...
has knowledge about the importance of open and reproducible science
has knowledge about the importance of power tests before an experiment
knows how a p-value should be interpreted alongside effect sizes
Skills
The candidate ...
can import data into R and process it reproducibly
can select and apply appropriate statistical models, check whether the model's assumptions are met, and interpret the results
can choose and make appropriate data visualisations
can design experiments or observational studies, including making considerations of statistical power
General competence
The candidate ...
is able to translate between scientific hypotheses and statistical hypotheses
is proficient in the programming language R
is able to write the statistical part of the Methods and Results section of a manuscript
ECTS Credits
5 ECTS
Level of Study
Masternivå eller masterdel av 5-årige integrerte masterprogram (må ha oppnådd 180 studiepoeng)
Semester of Instruction
Autumn.
This course has a limited capacity, enrolment is based on application. The application deadline is Wednesday in week 33 for the autumn semester. Please see this page for more information.
You will receive confirmation of whether you received a seat in Studentweb no later than Monday in the week 34.
It is compulsory to attend the first lecture/orientation meeting, or you risk losing your seat. If you are unable to attend the first lecture, you must contact the Study Section (studie.bio@uib.no). The time of the first lecture/orientation meeting can be found in the schedule linked below "Resources" or on Mitt UiB.
Place of Instruction
Bergen
Required Previous Knowledge
Bachelor's degree in biology or equivalent. The course is limited to master programme students at the Department of Biological Sciences. Students in integrated 5-year master's programs are required to have passed 180 ECTS in order to gain access to the course.
Recommended Previous Knowledge
7,5-10 ECTS in an introductory course (bachelor level) in Statistics, like STAT101 Elementary Statistics, STAT111 Statistical Methods, or a similar course.
Credit Reduction due to Course Overlap
None
Access to the Course
The course is limited to master programme students at the Department of Biological Sciences who have fulfilled the prerequisites. Students in integrated 5-year master's programs are required to have passed 180 ECTS in order to gain access to the course.
Teaching and learning methods
22 hours of lectures (theory)
22 hours in data labs (practical exercises)
Compulsory Assignments and Attendance
Attendance at lectures
Participation in data labs
Approved compulsory activities are valid for 3 semesters, including the semester of completion.
Forms of Assessment
Portfolio assessment, consisting of the 5 best rated individual assignments out of 6 assignments. The assignments that are part of the portfolio assessment are to be completed individually.
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade, grade F is a fail.
Assessment Semester
Autumn. The portfolio assessment is only held in semesters when the course is taught.
Reading List
The literature list will be available 1st of June for autumn semester and 1st of December for the spring semester.
Course Evaluation
Students will evaluate the course in accordance with the quality assurance system at UiB and the Department. You can find course evaluations in the Quality Assurance Reports.
Examination Support Material
The assignments that are part of the portfolio assessment are to be completed individually. Using support material is permitted.
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course Administrator
The Faculty of Science and Technology - Department of Biological Sciences has the responsibility for the course and study programme
Course description
Contact Information
This course is administered by the Department of Biological Sciences.
