CHOICE2

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

Synthetic content of the EU:

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

Type of topics:

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

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

Methods of control of knowledge:

The teaching is based on a problem-based learning approach, and students are evaluated on the way they progress in building their approach (40% of CC), as well as on their ability to present and defend their project during a final oral (60% of the overall grade)."

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"This module presents 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; (dis)similarity indices, distance; correlation"

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