2020-2021 / ENVT3024-1

Environmental data processing

Duration

24h Th, 24h Pr

Number of credits

 Master in environmental science and management (120 ECTS)4 crédits 
 Master in environmental science and management (60 ECTS)4 crédits 

Lecturer

N..., Anne-Claude Romain

Coordinator

Anne-Claude Romain

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course focuses on learning the R language in order to carry out statistical tests of parametric or non-parametric types as well as the development of models. Hypothesis testing will be approached from a theoretical and applied point of view. The learning of different models will also be discussed (principal component analysis; simple, multiple, orthogonal and logistic regression). The student will import a data set into the R software, manipulate it in order to submit it to different tests (or model building) and extract graphs for visual analysis. Critical thinking about the results will also be part of the learning process.
 

Learning outcomes of the learning unit

Train the student to produce relevant information for decision support from a sample of raw data (measurements or field observations). In addition, the student will learn how to manipulate and write codes in the R programme.

Prerequisite knowledge and skills

The student is expected to have a basic knowledge of mathematics (secondary school level), statistics (baccalaureate level) and is able to manipulate a computer.

Planned learning activities and teaching methods

The course is a succession of theoretical courses followed by practical work under the leadership of the Professor, and then in the form of exercises to perform alone or group depending on the case.

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

Face-to-face for theoretical courses and practical works. The entire course is available on the eCampus platform.

Organisational adjustments related to the current health context

Adaptations of distance learning courses are possible depending on sanitary conditions. The courses will be given on the Collaborate platform.

Recommended or required readings

None

Assessment methods and criteria

Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.

The knowledge test consists of a practical exercise that the student carries out on his/her laptop computer (the exercise is provided by the end of the first term at the latest). The student must send (to the teacher's e-mail address) 2 days before the oral exam (face-to-face or distance learning) a report that he or she will defend during an oral exam. This report is open book, however, during the oral examination questions on theory and the use of the R programme will be asked and closed book.
 

Work placement(s)

None.

Organizational remarks

None.

Contacts

cfalzone@uliege.be