Duration
24h Th, 24h Pr
Number of credits
| Master in environmental science and management (120 ECTS) | 4 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
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 and 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 (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 and statistical 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.
Recommended or required readings
None
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Additional information:
The control of knowledge consists in the formatting and realization of an analysis of a data base provided to the student. The work is to be done on computer (the exercise is provided by mid-December at the latest). The report must contain the work done (results, discussion, conclusion), the R code is provided in parallel. The student is allowed to use resources such as the course or the internet to complete the work.
The oral exam consists of the presentation of the work. The student will also be asked questions related to the handling of the program and the theory seen in class.
- Submission of the exercise by the professor: mid-December at the latest.
- Submission of the report by the student: 5 days before the oral defense by email, in case of failure to meet the deadline, the professor has the option of not allowing the student to present the oral.
Work placement(s)
None.
Organisational remarks and main changes to the course
None.
Contacts
cfalzone@uliege.be