7.00 credits
45.0 h + 40.0 h
Q1
Teacher(s)
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.
Learning outcomes
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. |
Teaching methods
Formal lectures and exercices sessions.
An introduction to a data analysis software will be proposed during the practicals.
A MOOC and exercices sessions about this MOOC will also be part of this course.
In 2020-2021, the course will be organised in a "comodal" way, so both in presential and with a live broadcast via Teams. However, for the students for whom it is not problematic (no quarantine, no symptoms, ...) the presence in the auditorium is advised. In case the number of places would not be sufficient, the professor will organise a registration system.
An introduction to a data analysis software will be proposed during the practicals.
A MOOC and exercices sessions about this MOOC will also be part of this course.
In 2020-2021, the course will be organised in a "comodal" way, so both in presential and with a live broadcast via Teams. However, for the students for whom it is not problematic (no quarantine, no symptoms, ...) the presence in the auditorium is advised. In case the number of places would not be sufficient, the professor will organise a registration system.
Evaluation methods
The evaluation includes a theoretical part and a practical part (student can have a recap form).
Furthermore, a continuous evaluation will be organised via short tests during the practicals sessions as via a project linked to the MOOC
Furthermore, a continuous evaluation will be organised via short tests during the practicals sessions as via a project linked to the MOOC
Other information
Prerequisites: Basic courses in mathematics (PHY1114 - PHY1115 or equivalent).
Online resources
All required ressources for the courses and the practicals willbe made available online via the Moodle page of the course.
The students will be granted an access to the MOOC "Penser Critique".
The students will be granted an access to the MOOC "Penser Critique".
Teaching materials
- matériel sur moodle
Faculty or entity
VETE
