- ECTS credits5
- Teaching semesterSpring
- Course codeBIO302
- Number of semesters1
This course has a limited capacity, enrolment is based on application. The application deadline is Wednesday in week 2 for the spring semester. Please see this page for more information. You will receive confirmation of whether you received a seat in Studentweb no later than Monday the week after the deadline.
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 (<email>email@example.com</email>). The time of the first lecture/orientation meeting can be found in the schedule on the course website or on Mitt UiB.
Objectives and Content
The course introduces some statistical tools for regression analysis. It consists of lectures and computer based practicals, beginning with ordinary least squares and then developing other regression methods that allow the assumptions of ordinary least squared to be relaxed. The course is followed by a take home exam which covers both theoretical and practical aspects of the course.
After completing the course, students should be able to:
- Describe the estimator in ordinary least squares
- Explain the assumptions of ordinary least squares and the consequences of violating these assumptions
- Recognise when assumptions ordinary least squares are violated
- Choose appropriate regression techniques given the properties of the data
- Interpret regression diagnostics and plots
- Build parsimonious models
- Make predictions with confidence intervals
- Analyse data in a modern statistical package
- Have some of the statistical skills necessary for their thesis projects
Required Previous Knowledge
Bachelor in Biology or equivalent.
Recommended Previous KnowledgeBIO300B Biostatistics (5 ECTS) or equivalent.
Compulsory Assignments and Attendance
Seminars. Approved compulsory activites are valid for 6 semesters, included the semester of completion.
Forms of Assessment
Written take-home exam on a given dataset.
The grading scale used is A to F. Grade A is the highest passing grade, grade F is a fail.
Exam only in semesters with teaching.
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.
Type of assessment: Take-home examination
- Withdrawal deadline