2023-2024 / ENVT3124-2

Environmental data processing, Part 2: Introduction to R


6h Th, 12h Pr

Number of credits

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


Anne-Claude Romain

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The student will be introduced to R through the RStudio interface. The basic notions of coding will be taught. They will carry out statistical processing using lines of code. He will also be introduced to the basic notions of RMarkdown.

Course content :

  • Introduction to coding,
  • Introduction to database management,
  • Recall of the basic notions of statistics and translation into lines of code,
  • Introduction to basic graphing in RStudio,
  • Reminder of the hypotheses and statistical tests and translation into lines of code,
  • Performing linear regressions using RStudio.
Each course has both practical and theoretical parts.

Learning outcomes of the learning unit

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

  • use the open source program R through the RStudio interface with the help of programming lines,
  • import a file into their workspace,
  • carry out the basic statistics seen in part 1,
  • search the internet for information on coding,
  • render the result(s) in a report generated with RMarkdown.

Prerequisite knowledge and skills

In general terms:

  • Knowledge of how to use a computer
  • Basic knowledge of Excel
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 course consists of a theoretical part with an application directly in practical format. It is essential for the student to follow the course as RMarkdown concepts will be introduced throughout the course to prepare the student for the examination.

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

Face-to-face course

Recommended or required readings

Basic knowledge of Exce:


Exam(s) in session

Any session

- In-person

written exam ( open-ended questions )

Additional information:

Additional information:

The examination deals with both partim 1 and partim 2, which are evaluated together.

The assessment focuses on the correct use and understanding of the statistical methods, the interpretation of the results as well as the use of the statistical software R.

The files resulting from the student's work must be submitted, all together, in a single file submitted, within the allotted time, on the partim 2 e-campus platform at the end of the exam.

The exam consists of a practical examination in R/R Markdown (statistical analyses), including questions on the good understanding of the theory (justification of choices, explaining techniques, interpreting results, ...).

During the examination, students can either work on their own laptop or on a university computer. The examination is an open book examination.

Any attempt at fraud will result in a zero rating. In particular, mobile phones are strictly forbidden all along the exam.

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.


Claudia Falzone: cfalzone@uliege.be

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