Høst 2019

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

The course is administrated by

Norges fiskerihøgskole

Type of course

This cource is obligatory in the Master's programme in International Fisheries Management (IFM). The course can also be taken as a singular course.

Course overlap

FSK-2020 Sustainable fisheries 10 stp

Course contents

Course contents

The course covers basic statistical theory and the quantitative and qualitative analysis of biological and economic information as well as methods used in social sciences related to fisheries management. Students are drilled in data retrieval, treatment, analysis and presentation, using simple and widely available software.

Application deadline

Applicants from Nordic countries: 1 June for the autumn semester. Exchange students and Fulbright students: 15 April for the autumn semester.

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 business-like 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

General competences:

communicate findings of analyses to support decision-making

Relevance for study program:

The course provides a practical background for scientific analysis and reporting in a multidisciplinary environment.

Language of instruction

The language of instruction and all syllabus material is English.

Teaching methods

Lectures, seminars, workshops, computer labs, peer-teaching, simulations, flipped-classroom and formative assessment.

The learning outcomes are effectively achieved through active student participation. Students are expected to prepare before every session.

Assessment

The course has portfolio assessment. Three reports together count 50% and essay (home exam) counts 50% of final grade. The grading scale is A-F, where A-E is passed, and F is failed.

Submission of reports and essay: electronically.

Portfolio

Written report on quantitative methods assignment (max. 3 pages, without references and annexes).
Written report on qualitative methods assignment (max. 3 pages, without references and annexes).
Written or video report on modelling assignment (if written report, max. 3 pages, without references and annexes).
Final essay (home exam) on given topic (two weeks) (max. 10 pages, without references and annexes).

Work requirements

Up to five written reports on quantitative methods assignments (all these have to receive the qualification "passed" before the submission of the final exam) (each report max. 2 pages, without references and annexes).
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 essay (on given topic) (group presentation, max. 20 min).

A re-sit exam will be arranged in the next semester.