Duration
Partim 1 : Introduction à la démarche statistique et statistique univariée : 12h Th, 12h Pr
Partim 2 : Statistiques bivariées : 6h Th, 6h Pr
Number of credits
| Master in agroecology (120 ECTS) | 3 crédits | |||
| Master in environmental science and management (120 ECTS) | 3 crédits |
Lecturer
Partim 1 : Introduction à la démarche statistique et statistique univariée : N...
Partim 2 : Statistiques bivariées : N...
Substitute(s)
Partim 1 : Introduction à la démarche statistique et statistique univariée : Laurent De Rudder
Partim 2 : Statistiques bivariées : Laurent De Rudder
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
The course presents some elementary statistical methods for environment.
It presents the main steps of a statistical analysis, tools for descriptive statistics and methods of statistical inference (including point estimation, confidence intervals and tests). We will focus in the first section on univariate statistics. In the second section, methods in multivariate statistics will be approached
The students will also learn how to use a statistical software in the section section.
Partim 1 : Introduction à la démarche statistique et statistique univariée
The course presents some elementary statistical methods for environment.
It presents the main steps of a statistical analysis, tools for descriptive statistics and methods of statistical inference (including point estimation, confidence intervals and tests). We will focus in the first section on univariate statistics. In the second section, methods in multivariate statistics will be approached
The students will also learn how to use a statistical software in the section section.
Partim 2 : Statistiques bivariées
The course presents some elementary statistical methods for environment.
It presents the main steps of a statistical analysis, tools for descriptive statistics and methods of statistical inference (including point estimation, confidence intervals and tests). We will focus in the first section on univariate statistics. In the second section, methods in multivariate statistics will be approached
The students will also learn how to use a statistical software in the section section.
Learning outcomes of the learning unit
- Understanding and using elementary statistical tools.
- Understanding simple statistical results in context.
- Understanding the scope of statistical studies
- Having the needed vocabulary/background to be able to interact with a statistician
- Knowing how to use a statistical software and how to interpret its outputs (Second section)
Partim 1 : Introduction à la démarche statistique et statistique univariée
- Understanding and using elementary statistical tools.
- Understanding simple statistical results in context.
- Understanding the scope of statistical studies
- Having the needed vocabulary/background to be able to interact with a statistician
- Knowing how to use a statistical software and how to interpret its outputs (Second section)
Partim 2 : Statistiques bivariées
- Understanding and using elementary statistical tools.
- Understanding simple statistical results in context.
- Understanding the scope of statistical studies
- Having the needed vocabulary/background to be able to interact with a statistician
- Knowing how to use a statistical software and how to interpret its outputs (Second section)
Prerequisite knowledge and skills
Notions of mathematics
Partim 1 : Introduction à la démarche statistique et statistique univariée
Notions of mathematics
Partim 2 : Statistiques bivariées
Notions of mathematics
Planned learning activities and teaching methods
Lectures and exercices
Partim 1 : Introduction à la démarche statistique et statistique univariée
Lectures and exercices
Partim 2 : Statistiques bivariées
Lectures and exercices
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face
Partim 1 : Introduction à la démarche statistique et statistique univariée
Theoretical lessons will be given online with lifesize. Exercices will be given face-to-face in Arlon.
Partim 2 : Statistiques bivariées
Theoretical lessons will be given online with lifesize. Exercices will be given face-to-face in Arlon.
Organisational adjustments related to the current health context
Recommended or required readings
Course notes and exercises are available through MyULG.
Partim 1 : Introduction à la démarche statistique et statistique univariée
Course notes and exercises are available through eCampus.
Partim 2 : Statistiques bivariées
Course notes and exercises are available through eCampus.
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.
Assessment during the examination session (if the sanitary conditions does not permit presence at the University, the exam will be "on line" with eCampus platform).
Partim 1 : Introduction à la démarche statistique et statistique univariée
Assessment during the examination session. If the situation does not allow the organisation of an exam, the students will be evaluated with eCampus.
Partim 2 : Statistiques bivariées
Assessment during the examination session. If the situation does not allow the organisation of an exam, the students will be evaluated with eCampus.
Work placement(s)
Organizational remarks
Contacts
Laurent De Rudder
Université de Liège
Département de Mathématique, B37
l.derudder@uliege.be
Partim 1 : Introduction à la démarche statistique et statistique univariée
Laurent De Rudder
Université de Liège
Département de Mathématique, B37
l.derudder@uliege.be
Partim 2 : Statistiques bivariées
Laurent De Rudder
Université de Liège
Département de Mathématique, B37
l.derudder@uliege.be