Competencies and objectives

 

Course context for academic year 2018-19

A partir de los conocimientos estadísticos básicos adquiridos en los gados, se debe ampliar los conocimientos del fundamento de la Estadística y de sus principales métodos aplicables en las pesquerías. Así, aprender a aplicar los conocimientos de Estadística a problemas reales es uno de los principales pilares para ampliar la capacidad de desarrollo de proyectos experimentales del alumnado. Además, conocer las herramientas que permiten resolver esos problemas y adquirir experiencia en el uso de las bases de datos más relevantes a nivel internacional, les ayudará a desarrollar dicha capacidad. Les permitirá identificar de manera correcta las variables y factores bajo estudio, elaborar diseños experimentales adecuados para las hipótesis establecidas y que además permitan optimizar el análisis.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees)

General Competences (CG)

  • CG0 : Developing good public speaking skills.
  • CG10 : Being skilled in the preparation of synthesis and presentation documents, and has experience in the preparation and presentation of oral communications and public defence.
  • CG3 : Knowing how to work in groups and foster attitudes of exchange and collaboration with other students, researchers and professionals.
  • CG4 : Knowing how to function in a multidisciplinary and multicultural environment.
  • CG5 : Being able to search for scientific and/or technical information and process it selectively.
  • CG9 : : Knowing how to communicate reasoning and conclusions to both a general audience and a specialised audience.

 

Specific Competences (CE)

  • CE23 : Being aware of the importance of fisheries statistics programmes within management plans, and understand the links that exist between the planning of management policies and strategies and the data necessary to provide answers.
  • CE24 : Knowing the basic statistical principles relevant to the analysis of fisheries data, and becoming familiar with the operation of computer software useful in such analysis.
  • CE25 : Examining the different types of data, the methods for their collection and the theoretical elements of the design and application of fisheries statistical systems.
  • CE26 : Becoming familiar with the fundamental principles of sampling that have a direct effect on the reliability of the statistics produced.
  • CE27 : Acquiring experience in the use of the most relevant international databases.

 

Basic Competences and Competences included under the Spanish Qualifications Framework for Higher Education (MECES)

  • CB6 : Acquiring and understanding knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
  • CB7 : Being able to apply acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.
  • CB8 : Being able to integrate knowledge and deal with the complexity of making judgements on the basis of incomplete or limited information, including reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements.
  • CB9 : Being able to communicate conclusions and the ultimate knowledge and reasons that support them to specialised and non-specialised audiences clearly and unambiguously.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2018-19

  • Conocer las técnicas básicas del diseño muestral y planificación de los muestreos en el ambiente marino.
  • Conocer los principios estadísticos básicos relevantes para el análisis de datos de pesquerías, y familiarizarse con el funcionamiento del software informático de utilidad en dichos análisis.
  • Examinar los distintos tipos de datos, los métodos para su recopilación y los elementos teóricos del diseño y aplicación de los sistemas estadísticos pesqueros.
  • Adquirir experiencia en el uso de las bases de datos más relevantes a nivel internacional.
  • Conocer la aplicación de los Sistemas de Información Geográfica (SIG) a los datos pesqueros.

 

 

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General

Code: 43800
Lecturer responsible:
FORCADA ALMARCHA, AITOR SANTIAGO
Credits ECTS: 5,00
Theoretical credits: 0,80
Practical credits: 1,20
Distance-base hours: 3,00

Departments involved

  • Dept: MARINE SCIENCES AND APPLIED BIOLOGY
    Area: STATISTICS AND OPERATIONS RESEARCH
    Theoretical credits: 0,6
    Practical credits: 1,4
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught