Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
3 credits
22.0 h + 10.0 h
Q1
Teacher(s)
Draye Xavier (coordinator); Govaerts Bernadette;
Language
French
Prerequisites
Introduction to probability and statistics (typ. courses LBIR1203 and LBIR1204)
Main themes
Quantitative data analysis methods in bioengineering ' Variance analysis with one and more classification factors, crossed or nested ' Generalised linear models (classification and regression factors) ' Random effect and mixed models ' Least square and maximum likelihood methods ' Analysis of categorical datas
Content
Cf LBIRA2101.
Teaching methods
Course in auditorium
Introduction course to data importation in SAS
Practical courses prepared by the students, with a test half way during the semester
Introduction course to data importation in SAS
Practical courses prepared by the students, with a test half way during the semester
Evaluation methods
Written exam with methodological questions and exercices méthodologiques, case studies, SAS code writing. Allowed material: 20 pages summary (10 pages resto/verso).
Other information
This course can be given in English.
Online resources
Moodle
Bibliography
Documentation obligatoire disponible sur Moodle
- Transparents de théorie et d'exemples liés au cours
- Enoncés d'exercices
- Formulaire
- Transparents de théorie et d'exemples liés au cours
- Enoncés d'exercices
- Formulaire
Documentation facultative disponible sur Moddle
- Documentation SAS/STAT (PROC GLM et PROC MIXED)
- Documentation SAS/STAT (PROC GLM et PROC MIXED)
Faculty or entity
AGRO
