Competencies and objectives

 

Course context for academic year 2019-20

Esta asignatura se ubica en el módulo Fundamental y dentro de él en la materia "Inferencia Estadística". La asignatura recoge las bases de la inferencia estadística, y su correcta asimilación será imprescindible para entender los contenidos de otras asignaturas como Análisis de Datos (I y II), Procesos Estocásticos y Series Temporales. Nos ocuparemos de la metodología general que se utiliza para realizar inferencias, así como de su aplicación en los casos más directos. Insistiremos tanto en el aprendizaje de la aplicación correcta de las diferentes técnicas estadísticas como en la interpretación precisa de los resultados obtenidos. Cada concepto introducido será motivado mediante un ejemplo práctico que suscite el interés por parte de los alumnos. Se aprenderá a manejar la herramienta informática R para la obtención de cálculos y gráficos necesarios para llevar a cabo procedimientos inferenciales tales como intervalos de confianza y contrastes de hipótesis. En esta asignatura se utilizan conceptos y resultados vistos previamente en las asignaturas "Introducción a la Estadística" y "Probabilidad".

 

 

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.
  • CE3 : Assimilate the definition of a new mathematical object in terms of others already known and be able to use said object in different contexts.
  • 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.
  • CE8 : Develop programmes that solve mathematical problems using the appropriate computational environment for each particular case.

 

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 2019-20

No data

 

 

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General

Code: 25035
Lecturer responsible:
FAJARDO GOMEZ, MARIA DOLORES
Credits ECTS: 6,00
Theoretical credits: 1,32
Practical credits: 1,08
Distance-base hours: 3,60

Departments involved

  • Dept: MATHEMATICS
    Area: STATISTICS AND OPERATIONS RESEARCH
    Theoretical credits: 1,32
    Practical credits: 1,08
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught