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Høst 2020
FSK-3006 Model theory and data processing methods - 10 stp
The course is administrated by
Type of course
Course overlap
Course contents
The course covers basic statistical theory and the quantitative and qualitative analysis of structured and unstructured information related to fisheries management.
Students are drilled in data retrieval, treatment, analysis, and presentation, using simple and widely available software.
Relevance for study program: The course provides a practical background for scientific analysis and reporting in a multidisciplinary environment.
Application deadline
Admission requirements
Application code: 9371
Recommended entrance requirements are BIO-3556 Fishery Biology and Harvest Technology or similar background, and basic familiarity with quantitative methods.
Objective of the course
Intended learning outcomes:
Knowledge:
- apply basic quantitative methods to process, analyze, test hypotheses, and visualize structured and unstructured data (e.g. generalized linear models)
- apply basic qualitative methods to process, analyze, test hypotheses, and visualize structured and unstructured data (e.g. content analysis, conceptual frameworks)
- explain results of the data processing and data analysis methods that were used
- use simple models to represent systems and make forecasts
- familiarize with both academic and applied/business-context research and development environments
Skills:
- summarize and present qualitative and quantitative data
- perform statistical analyses using different software
- practice different oral and written communication skills
- practice time-management skills
General competences:
- communicate findings of analyses to support decision-making
Language of instruction
Teaching methods
Lectures, seminars, short visits, workshops, computer labs, peer-teaching, simulations, flipped-classroom, formative assessment.
The learning outcomes are effectively achieved through active student participation. Students are expected to prepare before every session.
Assessment
The exam consists of portfolio assessment. The grading scale is A-F, where A-E is passed, and F is failed.
Submission of reports and essay: electronically.
Portfolio
- 20% of the final grade: Three written reports on quantitative methods assignment (each report: max. 7 pages, without references and annexes). Each report will be graded individually and an average will be made.
- 15% of the final grade: One written report on qualitative methods assignment (max. 3 pages, without references and annexes).
- 15% of the final grade: One written or video report on modelling assignment (if written report, max. 3 pages, without references and annexes).
- 50% of the final grade: Final essay (home exam) on given topic (37.5 effort hours) (max. 10 pages, without references and annexes).
Work requirements
The following work requirements are mandatory. Each item will be evaluated with pass/fail. All requirements have to be passed in order for the student to be allowed to take the exam.
- Oral presentation on a given article (max. 20 minutes).
- Oral presentation on a given topic (quantitative method, qualitative method or modelling) (duration varies depending on the topic).
- Oral presentation on use of data analysis methods in own Master’s thesis (max. 20 minutes).
- Oral presentation of the final essay (on given topic) (group presentation, max. 20 min).
- Filling in an on-line time-sheet for all activities in the course.
A re-sit exam will be arranged in the next semester. A student may re-sit only the part of the portfolio that he/she has failed.
Date for examination
The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.