Applied Statistics and Data Science Project

Objective

The purpose of this course is to complete and perfect students' methodological training. It is a chance to put the courses in data analysis, statistics, econometrics and/or time series into practice using real data. Initially, students will concentrate on identifying a problem and describing the data available. They will then model the problem, estimate the parameters of interest and test several theoretical hypotheses.

The course takes the form of work in small groups under the guidance of a supervisor. Each group of students, working on a precise subject and precise data, must apply the techniques indicated above effectively and produce a summary document presenting the work and the conclusions.

The supervisor's role is to guide the students in their project and develop certain aspects of mathematical statistics as they arise. Finally, the supervisor helps the students use various methods or procedures in a statistical or mathematical software package (SAS, Stata, R, Gauss, Matlab).

Planning

The plan is defined by the supervisor, and the students must follow it, working together regularly. The status of the project is presented by the students during March in a progress report.

References

En statistique, le cours de Statistique 1 (voire de Statistique 2) de l'ENSAE Paris
En économétrie,le cours d'Econométrie 1 et d'Econométrie 2 de l'ENSAE Paris
En séries temporelles,le cours de séries temportelles linéaires de l'ENSAE Paris
En apprentissage statistique, le cours "Theoretical Foundations of Machine Learning"

Pour l'aspect code informatique, les fichiers d'aide R/Python présentés dans différents cours de l'ENSAE Paris.