Course: Introduction to Programming and Data Analysis in R (v2026)

• Title: Introduction to Programming and Data Analysis in R (v2026)

• Instructors: Filip Andras, Efraín García Sánchez

• Format: In-person

• Available spots: 30

• Duration: 25 in-person hours across 5 sessions, plus 5 hours of independent work

• Location: Seminar Room 4, Mind, Brain and Behavior Research Center (CIMCYC)

• Prerequisite: Basic knowledge of statistics

• The course will be taught in Spanish.

Description and Contents

This course is intended for doctoral students in the health sciences and provides a theoretical and practical introduction to programming and data analysis in R. Throughout the course, participants will learn the fundamentals of the language, as well as techniques for data manipulation, basic statistical analysis, data visualization, and the preparation of reproducible research reports.
The course is divided into five sessions that combine theory and practice:

Session 1 — Introduction to Programming in R

• Why learn to program?
• The R and RStudio environment.
• Basic programming elements.
• Workflow and best practices.
• Initial data exploration.

Sessions 2 and 3 — Data Processing

• Working with data in R.
• Data manipulation.
• The tidyverse suite of packages.

Sessions 3 and 4 — Introduction to Data Analysis in R

• t-tests.
• ANOVA.
• Linear regression.

Session 5 — Research Reports and Bring Your Own Data

• R Markdown/Quarto
• Data visualization.
• In the second half of the session, students will apply what they have learned to their own datasets.
• Q&A and troubleshooting.

Schedule 

Install R and RStudio on Your Computer

R is a free programming language and statistical computing environment widely used in scientific research for data analysis, statistical modeling, data visualization, and more. RStudio is an integrated development environment (IDE) for R that provides a user-friendly interface, including a code editor, console, package manager, results viewer, and support for generating reproducible reports with R Markdown. It makes working with R much easier.

Where to download:

• R: from the official R project website, selecting the installer appropriate for your operating system (Windows, macOS, or Linux).
• RStudio: from its official downloads page, selecting the "Desktop" version appropriate for your operating system.

Course materials

Course materials,including session slides, example code, and supplementary resources, are currently being prepared. Once available, they will be uploaded to this section.

Lecture sessions: 

• Session 1 (.pdf)
• Session 2 (.pdf)
• Session 3 (.pdf)
• Session 4 (.pdf)
• Session 5 (.pdf)

Practical sessions:

Solved exercises:

Registration

Registration must be completed through the form available the website of the Escuela de Doctorado de las Ciencias de Salud which will be active from March 19 to 26, 2026.

This activity is part of grant CEX2023-001312-M, funded by MICIU/AEI/10.13039/501100011033 and grant UCE-PP2023-11 funded by University of Granada.