Programming and data reporting in R

Teacher(s)

Bugli Céline; El Ghouch Anouar;

Language

French

Prerequisites

Students must have prior training in probability and statistics, including: mastery of descriptive statistics, knowledge of the main probability distributions, understanding of the foundations of statistical inference, familiarity with simple or multiple linear regression, and analysis of variance (ANOVA).
Students must also be able to use a personal computer effectively in an academic setting: file management, organization of a working directory, basic use of Windows, Word, Excel, web browser, and Moodle platform. They must be able to install software, navigate interfaces, and manage digital documents independently.
No prior knowledge of R or any other programming language is required; the course is designed to gradually support the acquisition of these skills.

Main themes

This course is designed for students with or without prior programming experience who wish to develop practical skills in this field. It aims to provide a structured progression toward mastering statistical programming in R, by applying the language’s fundamental concepts, development best practices, and modern tools for scientific production.
The core pedagogical objective is to enable each student to achieve genuine autonomy in designing, implementing, and disseminating reproducible statistical analyses. By the end of the course, students should be able to:

• Efficiently process and transform data;
• Create high-quality graphs tailored for scientific communication;
• Write their own R functions;
• Design and structure an R package;
• Produce automated and dynamic reports using Quarto and/or Shiny.

The course is based on independent and self-directed work, supported throughout the process by the teaching team.

Faculty or entity

> LSBA