Competencies and objectives

 

Course context for academic year 2021-22

Esta asignatura se ubica en el módulo Avanzado y dentro de él en la materia "Análisis de Datos y Álgebra Aplicada". Dicha materia incluye además las asignaturas: "Teoría de Códigos", “Análisis de Datos II” y “Criptografía”. Los objetivos de la asignatura, en consonancia con la naturaleza de sus contenidos, son: (1) presentar una introducción sistemática de los principales modelos de procesos estocásticos, profundizando en el estudio de sus propiedades, e ilustrando su potencial como herramientas de modelización; (2) atraer el interés de los estudiantes hacia la rica diversidad de aplicaciones de los procesos estocásticos; (3) familiarizar al alumno con las sutilezas matemáticas presentes en esta brillante teoría. Los conocimientos previos requeridos para cursar con éxito la asignatura son los fundamentos de probabilidad que se adquieren en las asignaturas de “Introducción a la Estadística”, y “Probabilidad”. Es aconsejable, aunque no imprescindible, un buen conocimiento de las nociones básica de inferencia estadística (que se imparten en la asignatura de “Inferencia Estadística”).

 

 

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

Specific Competences (CE)

  • CE1 : Understand and use mathematical language. Acquire the capacity to enunciate propositions in different fields of Mathematics, to construct demonstrations and transmit the mathematical knowledge acquired.
  • CE10 : Communicate, both orally and in writing, mathematical knowledge, procedures, results and ideas.
  • CE11 : Ability to solve academic, technical, financial and social problems using mathematical methods.
  • CE12 : Ability to work in a team, providing mathematical models adapted to the needs of the group.
  • CE14 : Solve qualitative and quantitative problems using previously developed models.
  • CE15 : Recognise and analyse new problems and prepare strategies to resolve them.
  • CE16 : Prepare, present and defend scientific reports both in writing and orally to an audience.
  • CE5 : Propose, analyse, validate and interpret models of simple real-life situations, using the most appropriate mathematical tools for the purpose.
  • CE6 : Solve mathematical problems using basic calculus skills and other techniques, planning their resolution according to the tools available and any time and resource restriction.
  • CE7 : Use computer applications for statistical analysis, numerical calculus and symbolic calculus, graphic visualisation and others to experiment in Mathematics and solve problems.
  • CE8 : Develop programmes that solve mathematical problems using the appropriate computational environment for each particular case.
  • CE9 : Use bibliographic search tools for Mathematics.

 

Specific Generic UA Competences

  • CGUA1 : Understand scientific English.
  • CGUA2 : Possess computer knowledge related to the field of study.
  • CGUA3 : Acquire or posses basic ICT (Information and Communication technology) skills and manage the information obtained appropriately.

 

Generic Degree Course Competences

  • CG1 : Develop the capacity for analysis, synthesis and critical reasoning.
  • CG2 : Show the ability for effective and efficient direction/management: entrepreneurial spirit, creativity, organisation, planning, control, decision making and negotiation.
  • CG3 : Resolve problems effectively.
  • CG4 : Show ability for teamwork.
  • CG5 : Commitment to ethics, the values of equality and social responsibility as a citizen and as a professional.
  • CG6 : Learn autonomously.
  • CG7 : Show the ability to adapt to new situations.
  • CG9 : Demonstrate the ability to transmit information, ideas, problems and solutions to both specialist and non-specialist audiences.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2021-22

No data

 

 

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General

Code: 25060
Lecturer responsible:
TROTTINI, MARIO
Credits ECTS: 6,00
Theoretical credits: 1,12
Practical credits: 1,28
Distance-base hours: 3,60

Departments involved

  • Dept: MATHEMATICS
    Area: STATISTICS AND OPERATIONS RESEARCH
    Theoretical credits: 1,12
    Practical credits: 1,28
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught