TecnoCampus Foundation
eCampus
University Business
eCampus

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General information

Subject type: Mandatory

Coordinator: Sara González Millán

Trimester: Second term

Credits: 3

Teaching staff: 

Bruno Fernandez-valdes Villa
Victor Toro Roman 

Academic year: 2025

Teaching course: 1

Languages ​​of instruction

  • Spanish

There is content in the subject in English.

Competencies / Learning Outcomes

Basic skills

  • 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

  • CB7. That students know how to apply the knowledge acquired and their problem-solving ability in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of ​​study.

  • CB8. That students are capable of integrating knowledge and facing the complexity of formulating judgments based on information that, while incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments.

  • CB10. That students possess the learning skills that allow them to continue studying in a manner that will be largely self-directed or autonomous

     

Specific skills

  • CE9. Develop and defend research work in the field of personal training, injury and disease prevention and physical rehabilitation.

General competencies

  • CG1. Apply information and communication technologies in the context of personal training, injury and disease prevention and physical and sports rehabilitation

Transversal competences

  • CT1. Build critical thinking by analyzing one's own learning process and assertively and rationally discussing other people's and one's own ideas in an eloquent context.

  • CT2. Demonstrate the skills for cooperative work and participation in multidisciplinary teams in accordance with the principles of the code of ethics of their profession, incorporating attitudes such as effort, respect and commitment as a hallmark.

Presentation of the subject

This subject will allow students to acquire the necessary knowledge to carry out the analysis of data from research studies in the field of health prevention, personal well-being, physical education, sports performance, as well as sports planning, organization and management that allows them to obtain scientific evidence that ensures optimal results when this knowledge is applied to the general population.


In this process, the student will become familiar with the techniques and methods of statistical analysis, as well as with the most appropriate resources and technologies for carrying out this analysis. In addition, the student will learn to read and critically interpret the results evidenced in the different forms of scientific dissemination in their field. Statistics will allow students to describe the social, physiological and/or biomechanical factors that condition the practice of physical activity and sport.


The student will be able to prepare simple scientific papers and conduct searches following international standards. As well as improving professional practice with decision-making based on scientific evidence.

The classroom (physical or virtual) is a safe space, free of sexist, racist, homophobic, transphobic and discriminatory attitudes, either towards students or towards teachers. We trust that together we can create a safe space where we can make mistakes and learn without having to suffer prejudice from others. 

The use of AI in this subject is regulated in the learning plan.

Contents

  • Review of statistical concepts.
    • Bayesian statistics.
    • Probability distributions.
    • Hypothesis testing.
    • Confidence intervals.
    • Comparison of proportions and averages.
    • General linear model: univariate, multivariate, repeated measures.
    • Non-parametric tests.
    • Correlations.
    • Linear and logistic regression: estimation, selection and validation of the model. Sample size and statistical power.
    • Frequency measures (prevalence, incidence) and association (relative risk, absolute risk and Odds ratio).
  • Elaboration and preparation of data for subsequent statistical analysis. Introduction to Excel.
  • Introduction to the use of free software in statistics.
  • Use of artificial intelligence in statistics.
  • Descriptive statistics applied to sports sciences through free software.
  • Inferential statistics applied to sports sciences through free software.

Activities and evaluation system

The acquisition of skills by the student will be assessed through the continuous assessment system, weighing and evaluating the results obtained from the application of the assessment procedures described in each teaching plan of the subject.
The evaluation will conclude with a recognition of the level of learning achieved by the student, materialized in the numerical qualification, in accordance with the provisions of current legislation. Qualification system (Royal Decree 1125/2003, of September 5, which establishes the European Credit System and the qualification system for university degrees of an official nature and validity throughout the state territory):


0 - 4,9: Suspended (SS)
5,0 - 6,9: Approved (AP)
7,0 - 8,9: Notable (NT)
9,0 - 10: Excellent (EX)


The weighting established for the different evaluation activities is specified in:

The weighting established for the different evaluation activities is specified in Activity/subject

%

SEV2. Online questionnaires

 20%
SEV3. Participation in
online forums and discussions		  20%

SEV4. Individual work

 30%

SEV5. Online group work

 30%

Total

100%

In the individual sections, a minimum of 3 out of 10 must be achieved on average across all individual assessment activities in order to be able to average and pass the subject.

Bibliography

Basic

Barriopedro, MI & Muniesa, C. (2012). Data analysis in the sciences of physical activity and sport. pyramid

Casals, M., Fernández, J., Martínez, V., Lopez, M., Langohr, K., & Cortés, J. (2022). A systematic review of sport-related packages within the R CRAN repository. International Journal of Sports Science & Coaching, 17479541221136238.

Horton, NJ, & Kleinman, K. (2015). Using R and RStudio for data management, statistical analysis, and graphics. CRC Press.

Complementary

Grömping, U. (2015). Using R and RStudio for Data Management, Statistical Analysis and Graphics. Journal of Statistical Software, 68, 1-7.

Sánchez, D. (2010). Statistics applied to physiotherapy, sports sciences and biomechanics. Spain: CEU Ediciones

Severini, TA (2020). Analytic methods in sports: Using mathematics and statistics to understand data from baseball, football, basketball, and other sports. Chapman and Hall/CRC.

Van der Loo, MP (2012). Learning RStudio for R statistical computing. Packt Publishing Ltd.