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2025-2026 / ENVT3124-2

Environmental data processing, Part 2: Introduction to R

Duration

6h Th, 12h Pr

Number of credits

 Advanced Master in Risk and Disaster Management in the Anthropocene Era2 crédits 

Lecturer

Laurent Loosveldt

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The student will be required to use R through the RStudio interface. They will perform statistical processing using lines of code, while simultaneously being introduced to fundamental concepts of statistics.

Course content:

  • Introduction to data management and basic database exploration
  • Review of basic statistical concepts and their implementation in code
  • Introduction to creating basic graphs in RStudio
  • Basic concepts of statistical tests (context, errors, implementation, p-value, etc.) and their coding in R, with interpretation
  • Basic concepts of linear regression and its implementation using RStudio

Learning outcomes of the learning unit

At the end of this course unit, the student will be able to:

  • Use the open-source program R through the RStudio interface by writing code
  • Import a file into their workspace
  • Manipulate and explore a database
  • Perform basic statistical analyses
  • Carry out several statistical tests via the RStudio interface and interpret the results
  • Perform a linear regression using RStudio
  • Search online for information related to coding

Prerequisite knowledge and skills

In general terms:

  • Knowledge of how to use a computer
  • Basic knowledge of Excel
  • Basic knowledge of statistics (descriptive statistics)
If the student attends the course with his/her personal computer, he must:

  • Configure the keyboard correctly according to the keys (AZERTY or QUERTY)
  • Know how to install a computer program on his/her computer

Planned learning activities and teaching methods

A theoretical in-person lecture will be dedicated to explaining the fundamental concepts of statistical tests and linear regression.

One in-person exercise session will focus on database management, and a second in-person exercise session will address data manipulation.

The remaining teaching activities will be delivered through videos on the e-campus platform. In these videos, the theoretical concepts presented will be directly applied using the R software. Students will then be invited to test their understanding of these concepts and practice the R commands introduced through quizzes on e-campus.

Mode of delivery (face to face, distance learning, hybrid learning)

Blended learning


Further information:

Mix of in-person activities and video content on e-campus.

Course materials and recommended or required readings

Platform(s) used for course materials:
- eCampus


Further information:

The lecture notes and slides from the in-person theoretical sessions will be made available to students.

The remainder of the course will rely on videos available on the e-campus platform and tests to be completed on this platform.

Regarding basic Excel knowledge, we refer, for example, to the following site:

https://openclassrooms.com/fr/courses/7168336-maitrisez-les-fondamentaux-dexcel

Exam(s) in session

Any session

- In-person

written exam


Further information:

Specific note exclusively for students enrolled in the Advanced Master's in Risk and Disaster Management in the Anthropocene Era.

Students in this specialised master's programme who only take Part 2 of the course will be exempt from certain in-depth comprehension questions intended for students who have also completed Parts 1 and 3. The questions from which they are exempt will be clearly indicated on the exam paper.

Work placement(s)

Organisational remarks and main changes to the course

The student is requested to inform the teacher if he/she does not have a personal computer.

Contacts

Association of one or more MOOCs