FSK-3006 Model theory and data processing methods - 10 stp

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 code: 9371

Recommended entrance requirements are BIO-3556 Fishery Biology and Harvest Technology or similar background, and basic familiarity with quantitative methods.

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

Lectures, seminars, 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.

The course has portfolio assessment.     If not otherwise specified, 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: One written report on quantitative methods assignment (max. 7 pages, without references and annexes  
• 15% of the final grade: One written report on qualitative methods assignment (max. 4 pages, without references and annexes) 
• 15% of the final report: 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)  

There is organized feedback for all submissions (optional). The feedback session for the final portfolio item is held orally.  

Re-sit exam

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.  

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 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 (it includes presenting a self-chosen study that inspires the student’s work) (max. 30 minutes).

The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.