Quantitative methods III: data analysis

Teacher(s)

Marquis Nicolas; Robert Pierre-Olivier (compensates Marquis Nicolas);

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.

Learning outcomes

At the end of this learning unit, the student is able to :

For each statistical method seen during the course, students are expected to : - Master the conditions of statistical analysis (eg. Regarding inference) - Understand the operations, uses and pertinence of bi and multivariate techniques - Be able to produce, through SPSS software statistical outputs and be able to interpret them, with a accurate use of statistical vocabulary - Demonstrate ability to understand and deal with apprentice-researcher responsibility at every stage of statistical analysis

Teaching methods

The course will be given this year by distance learning. Videos will be posted on Teams no later than the morning of the day before the course, which students should review. Afterwards, a Teams meeting on specific Tuesdays from 10:45 to 11:45 will allow students to ask questions about the material as in a translated class.
The course will provide the theoretical elements necessary to master the different methods: understanding the ingredients, the logic, the conditions of use and the interpretation of the results. Starting from concrete problems, it will be as participatory as possible.
Description of the practical work (device(s) set up, service(s) expected from the students...) :
The practical exercises will take place according to modalities that are mostly distant and partly face-to-face, explained during the first session. They will mainly allow :
- The assessment of the mastery of theoretical elements studied during the course
- The practice of various methods through the SPSS software
- Exercises of interpretation on various outputs.
They will require active commitment and participations from the students. They will also be the opportunity for the students to ask the question they may have about the course, and to prepare the building of the deliverable (cf. below).

Evaluation methods

Students will be assessed 1) through a deliverable that will be a group assignement – instructions will be given during the first lesson and made available on Moodle (50% of the points) 2) through an 3h examination at the end of the term (50% of the points).
The global mark is the geometric average of the two parts:
√((PointsExamen/20)? (PointsTravail/20) )
The mark of the successful assessment (examination or work) may be retained, unless specifically requested by the student, during the same academic year.

Other information

At the university level, it is up to the students to decide wether they attend to the lessons or not. Teacher and assistants of course recommend a maximal attendance at both lessons and TPs. Except in the event of force majeure, non-attendance and its potential consequence are the student’s sole responsibility.
In the same way, students are free to organize their time during the academic year. Once again, we recommend a continuous assessment of the course comprehension AS WELL AS a continuous commitment in the deliverable.
Students who decide no to follow those instructions and who would unfortunately fail at the January examination round should be aware that no catching-up session will be organized in the second term, nor in ex-cathedra teaching, nor in informal meetings with teaching assistants. The course content, about which the students were allowed to ask questions during the first term will be considered as seen and understood.
Students who failed in January will of course be given the opportunity to get explanation about their deliverable and examination, but it is their sole responsibility to bring the needed improvement at June or August sessions.

Bibliography

Sera communiquée au fil du cours. Les slides seront rendus disponibles sur moodle.

Faculty or entity

> ESPB