Program Overview

Introduction to the Expert Course

The Expert course in Designing experiments and using mixed models in R is a response to the growing demand for advanced skills in planning and analyzing experiments in complex data environments. This course aims to deliver rigorous and practical content, supported by the use of the R platform, to empower participants to address scientific, professional, and cultural challenges effectively.

Objectives

The course objectives are to:

1. Understand the fundamentals of experimental design, including variable identification, hypothesis formulation, and experiment planning.
2. Master the use of R for statistical analysis, graph generation, and data visualization.
3. Apply mixed models to analyze data and make informed decisions.
4. Develop technical communication skills to present analysis results clearly and effectively.
5. Foster professional ethics in research and data management.
6. Promote interdisciplinary collaboration in research projects requiring advanced data analysis.
7. Update professional competencies in statistical methods and techniques.

Programme

The course programme includes the following modules:

• Introduction to experimental design
• Understanding mixed models
• Functions for using mixed models in R
• Mixed Models: Varied Experimental Data
• Carrying out case studies in class

Each module has specific learning outcomes and is compulsory (OB).

Recipients

This training is aimed at students with a previous university degree. Students enrolled in a Bachelor's or Double Degree with a maximum of 30 ECTS credits can access conditionally. Exceptionally, those without a previous official university degree but with work experience in the field can also access, though they will only be eligible for a diploma or university extension certificate.

Access Requirements

To take the course, participants need:

• Basic knowledge of R
• A laptop
• Recent versions of R and RStudio
• Specific R packages (installation instructions will be provided before the course)

Selection Criteria

In case of excess applications, selection will be based on:

1. Academic Qualification (40%): Relevance of the applicant's degree to the course content.
2. Professional Situation (30%): Current professional situation, with positive valuation for those working or researching in related fields.
3. Level of Studies (30%): Higher scores for those in advanced stages of their studies (Master's or PhD).

Number of Places

The course has 20 places available.

Academic Management and Faculty

• Academic Direction: Luis Cayuela Delgado
• Academic Secretary: Ra萖 Garc燰 Camacho

Duration and Development

• Modality: In-person
• Number of Credits: 3 ECTS credits
• Contact Hours: 30 hours
• Place of Delivery: Manuel Becerra
• Start and End Date: January 19-23, 2026

Reservation of Place and Enrollment

• Pre-registration Period: October 13, 2025, to January 15, 2026
• Enrollment Deadline: December 1 to January 15, 2026
• Title Price: 350 euros

The course start is conditioned on the minimum number of enrolled students.

Documentation to Attach, Forms, and Place of Delivery

Applicants must submit scanned documentation, including:

• National Identity Document or equivalent
• University Degree
• Curriculum Vitae
• Responsible declaration of veracity of the data provided
• Any other document required by the Academic Department of Continuing Education

Foreign qualifications require additional documentation, including a passport or residence card and a foreign Higher Education Degree.