Competencies and objectives

 

Course context for academic year 2025-26

The aim of this subject is to provide students with useful quantification techniques for the development and understanding of other subjects in the master's degree, to create in students the aptitudes and skills to deal critically, reflectively and scientifically with the volume of quantitative information and situations of uncertainty in their field of work, and to offer methodological support for students to tackle new scientific advances. The course covers the main statistical procedures, from the review of descriptive tools to the fundamentals and application of statistical inference techniques.

 

 

 

Learning outcomes / Course competencies (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2025-26

Skills/Skills

  • CB10 : Possess the learning skills that allow them to continue studying in a way that will largely be self-directed or autonomous.
  • CB9 : Know how to communicate their conclusions - and the knowledge and ultimate reasons that support them - to specialized and non-specialized audiences clearly and unambiguously.
  • CG4 : Know how to organize data in the preparation of clinical histories applicable to different population groups that present different visual care needs.
  • CT2 : Develop teamwork skills, whether in teams with personnel from the same discipline or multidisciplinary teams
  • CT3 : Develop skills related to computer tools and information and communication technologies

 

Conocimientos/Contenidos

  • CB6 : Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context.
  • CE5 : Know the principles and applications of the main tools of statistical inference in Health Sciences

 

Skills/Competences

  • CB7 : Know how to apply acquired knowledge and problem-solving abilities in new or little-known environments within broader (or multidisciplinary) contexts related to their field of study.
  • CB8 : Be able to integrate knowledge and face the complexity of forming judgments from information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments.
  • CE1 : Identify the general principles of experimental design and probabilistic models in the field of Health Sciences
  • CE4 : Know how to recognize a well-defined statistical problem in real problems in their professional field, developing testable hypotheses and models using the most appropriate analysis techniques
  • CE6 : Identify the fundamental techniques of data processing and analysis, analyzing and interpreting the results
  • CG5 : Acquire the capacity for information and resource management, reasoning, drawing conclusions, and scientific and technical autonomy
  • CT1 : Adopt the principle of respect for human rights and fundamental rights, respect for gender equality and non-discrimination based on any personal or social condition or circumstance, and respect for the principles of universal accessibility and design for all people

 

 

 

Learning outcomes (Training objectives)

 

1. Recognise the situations in which a statistical problem arises.
2. Create and manage health databases.
3. Apply information summarisation techniques appropriate to the data available.
4. Recognise situations of uncertainty and use the probability measure and associated probability models in each case.
5. Design and plan an investigation.
6. Select and apply the appropriate technique for data analysis according to the objectives of the investigation and the information available.
7. Use data analysis software.
8. Interpret and disseminate the results.

1. Recognise the situations in which a statistical problem arises.

2. Create and manage health databases.

3. Apply information summarisation techniques appropriate to the data available.

4. Recognise situations of uncertainty and use the probability measure and associated probability models in each case.

5. Design and plan an investigation.

6. Select and apply the appropriate technique for data analysis according to the objectives of the investigation and the information available.

7. Use data analysis software.

8. Interpret and disseminate the results.

 

 

 

Specific objectives stated by the academic staff for academic year 2025-26

1. Recognise the situations in which a statistical problem arises.

2. Create and manage health databases

3. Apply information summarisation techniques appropriate to the data available

4. Recognise situations of uncertainty and use the probability measure and associated probability models in each case.

5. Design and plan an investigation

6. Select and apply the appropriate technique for data analysis according to the objectives of the investigation and the information available.

7. Use data analysis software

8. Interpret and disseminate results

 

 

 

General

Code: 37930
Lecturer responsible:
Moncho Vasallo, Joaquín
Credits ECTS: 3,00
Theoretical credits: 0,60
Practical credits: 0,60
Distance-base hours: 1,80

Departments involved

  • Dept: Community Nursing, Preventive Medicine & Public Health and History of Science
    Area: Nursing
    Theoretical credits: 0,6
    Practical credits: 0,6
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught