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Course description
  DATA ANALYSIS II

Competencies and objectives

 

Course context for academic year 2013-14

Esta asignatura se ubica en el módulo Fundamental y dentro de él, en la materia Optimización. La asignatura recoge el estudio y aplicación de las técnicas de análisis de datos detalladas en los contenidos.

Análisis de datos II es una ampliación de la asignatura Análisis de datos I. En esta asignatura se pretende desarrollar con más detalle las técnicas de dependencia con enfoque inferencial que se introdujeron en la asignatura anterior. Por este motivo la asignatura empieza con la introducción de las distribuciones multivariantes y la inferencia sobre vectores de medias. Los modelos de regresión se verán ampliados por los modelos lineales generalizados, en los que la respuesta no sigue una distribución normal. Además se abordará el caso en el que la variable respuesta es multivariante, en el que se pretenden establecer relaciones entre dos matrices de datos.

 

 

 

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.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2013-14

 

 

General

Code: 25062
Lecturer responsible:
NUEDA ROLDAN, MARIA JOSE
Credits ECTS: 6,00
Theoretical credits: 1,00
Practical credits: 1,40
Distance-base hours: 3,60

Departments involved

  • Dept: STATISTICS AND OPERATIONS RESEARCH
    Area: STATISTICS AND OPERATIONS RESEARCH
    Theoretical credits: 1
    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