CHOIX2

"The aim of this course is to consolidate students' grounding in ecology and/or evolution by inviting them to define a research topic and question(s), by defining relevant hypotheses in a well-argued manner, and by justifying a strategy for acquiring and analyzing the data needed to test them.

Synthetic content of the EU:

- Independent tutored work: identification of a relevant scientific question; bibliographical synthesis to establish the state of the art and justify scientific hypotheses; proposal and justification of a methodological approach (materials and methods) to test the proposed hypotheses.

Type of subject:

The topics can be based on any question identified by the students (in groups of 3/4), and validated by the teaching team, and draw on different approaches to suit the expectations of the different courses. For example, students may propose a field or experimental sampling strategy, a meta-analysis of literature data, an analysis of sequences retrieved from GenBank, an analysis of occurrence data retrieved from GBIF, etc.

In all cases, projects must involve a genuine data acquisition strategy, identified, justified and described by the students in the materials and methods requested in M1S2, with a provisional timetable for the project's progress and identification of the tasks that each student will carry out within each group as part of the project's implementation in M2S3. Projects must also be financially realistic, with a provisional budget, and must be able to be finalized within the time available in M2S3.

Assessment of knowledge:

Teaching is based on a problem-based learning approach, and students are assessed on how they progress in constructing their approach (40% of CC), as well as on their ability to present and defend their project at a final oral (60% of the overall mark)."

See full page

"This module introduces table management and the link between multivariate and univariate: matrix manipulation and common operations; notion of projection and distance; translation of descriptive and univariate statistics with multiple regression/ACP/AFD as an example; indices of (dis)similarity, distance; correlation".

See full page