6 credits
45.0 h + 30.0 h
Q1
Teacher(s)
Francq Bernard (compensates Legrand Catherine); Legrand Catherine;
Language
French
Prerequisites
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
- Introduction to probability ; discrete (binomiale, multinomial and Poisson) and continuous (normal, chi-square, Student and Fisher-Snedecor) distributions. - Descriptive statistics (measures of location and dispersion, empirical distribution, histograms, graphs, dependence measures and their graphical representations) - Introduction to statistical inference: point estimation, confidence intervals, hypothesis tests ; application to the comparison of means and variances. - ANOVA I and ANOVA II models. - Linear models : linear and multiple regression. - Simple, partial and multiple correlations. - Inference methods for discrete data and contigency tables. - Introduction to the planning of experiments.
Aims
At the end of this learning unit, the student is able to : | |
| 1 | The goal of that course is to introduce students in veterinary science to the rational use of statistical methods for the analysis of data in their discipline. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Other information
Prerequisites: Basic courses in mathematics (PHY1114 - PHY1115 or equivalent). Evaluation : the evaluation includes a theoretical part and a practical part as well as project. An introduction to a data analysis software will be proposed during the practicals.
Faculty or entity
VETE
