lbira2101a  2017-2018  Louvain-la-Neuve

3 credits
22.0 h + 10.0 h
Q1
Teacher(s)
Draye Xavier coordinator; El Ghouch Anouar; 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
Table of content
Introduction
Models for a quantitative response and one fixed factor
'        Linear model with one quantitative factor
'        Polynomial and non linear model
'        Variance analysis with one fixed factor
Linear models for one quantitative response and two fixed factors
'        Variance analysis with two crossed fixed factors
'        Multiple linear regression
'        Covariancer analysis and general linear model
Variance components models
'        Variance analysis with one random factor
'        Estimation of random effects and variance components
Mixed linear models
'        Formulation of random effects and structure of the covariance matrix
'        Analysis of common mixed models in biology (genetics, experimental design)
'        Analysis of longitudinal data
'        Covariance analysis in mixed models
Models for categorical data (not included in LBIRA2101A)
'        Contingency tables
'        Logistic regression
'        Generalised linear models
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
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
Documentation facultative disponible sur Moddle
-        Documentation SAS/STAT (PROC GLM et PROC MIXED)
Faculty or entity
AGRO


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Forests and Natural Areas Engineering

Master [120] in Environmental Bioengineering