Statistical Analysis with R: Language and Graphics

Statistical Analysis with R: Language and Graphics

Overview

This micro-credential introduces the fundamentals of the R language and its data structures, enabling the student to import, export, debug and transform data, laying the foundation for the analysis and efficient manipulation of information.

Goals

  • To understand the fundamentals of the R language and its data structures. 
  • Learn to import and export data, as well as clean and transform it.

Access requirements

  • To hold an official Spanish university degree or another degree issued by a higher education institution belonging to another Member State of the European Higher Education Area, which qualifies for access to master's level studies in that State.
  • Holding a degree issued by an educational system outside the European Higher Education Area without official recognition or a declaration of equivalence. In these cases, the academic director will submit a report to the Academic Committee, which will authorize or deny admission. Under no circumstances will authorization imply official recognition of the foreign degree, nor its recognition for any purpose other than pursuing postgraduate studies at the ULL.

Academic program

Contents

  1. The R and RStudio console. Environment management. Variables, functions, and basic arithmetic.
  2. Vector arithmetic. Data structures: vectors, arrays, and lists. 
  3. Data structures: data frames. Importing and exporting data. 
  4. Programming basics: conditionals, control structures, and functions. 
  5. Executing code in the console and in RStudio. Random variables. Sampling and simulation. 
  6. Report writing with R Markdown and Quarto. 
  7. Data preprocessing and manipulation with dplyr. 
  8. Basic graphics in R: graphics. High-level and low-level interactive functions. 
  9. The ggplot2 package and its graphics language: data, aesthetics, and geoms.

Methodology and activities

  • Lectures/expository method: presentation or explanation by the teaching staff.
  • Practical classes: activities supervised by the teaching staff in the classroom, laboratories, clinics.
  • Assessment: written tests, oral tests, practical tests…
  • Tutoring: instruction period in which teachers and students interact with the aim of reviewing and discussing materials and topics presented in class.

Evaluation criteria

  • Written works, memoirs, internship reports, and projects: a document prepared on a topic or activity carried out, following the instructions established by the teaching staff.
  • Oral presentation and defense of topics, assignments, final projects, etc.: oral presentation on a topic related to the course content or on the results of an assignment, exercise, or project, followed by a discussion with the teaching staff. This can be done individually or in a group.

General information

Credits: 4 ECTS

Duration: 23/02/26-16/03/2026

Teaching modality: In person

Location: Faculty of Sciences, Biology Section

Registration

More information

Flexibility

Short courses available in various formats (in-person, online, or hybrid). Ideal for learning without interrupting your professional life.

Employability

Content created and delivered by professionals and experts in the field, designed for immediate application.

Certification

Endorsed by the University of La Laguna. You will receive an official ECTS certificate, valid in the European Higher Education Area.

Teaching staff

Carlos González Alcón

Profesor de matemáticas, ha trabajado en modelos de crecimiento económicoaportaciones desde la teoría de los juegos dinámicos, así como en aplicaciones de la modelización a la biotecnología y biomedicina.

José Ramón Arévalo

Catedrático de Ecología de la Universidad de La Laguna. Interesado en el análisis del impacto en la diversidad y estructura de la comunidad de las perturbaciones intrínsecas y extrínsicas al ecosistema.

Natalia Sierra

Investigadora postdoctoral del área de Ecología de la Universidad de La Laguna. Interesada en la respuesta de las comunidades vegetales a los cambios de clima y adaptaciones fisiológicas al mismo.

Itahisa Marcelino

Profesora e investigadora en el ámbito de las Ciencias de la Salud, con especialización en bioinformática, genómica y epidemiología. Su actividad investigadora se centra en la aplicación de herramientas computacionales y enfoques epidemiológicos.

Tuition

Tasa de matriculación

200€
Price per credit €50

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