The Master 2 in Statistics and Econometrics is open to students who have already acquired a solid grounding in economics and / or mathematical statistics. It consists of general classes in mathematical statistics and econometrics and specialised classes in various fields of application. The objective of the course is firstly to provide students with a solid culture in the major areas of applied statistics. Acquiring this culture clearly has to go hand-in-hand with learning how to handle various software applications, with a particular focus on SAS, R and Matlab. Students will also acquire IT skills in database management. Options are available to help them gain a further insight into applications in a number of fields, not least the tertiary sector.
This course is intended to lead to careers in statistical studies, actuarial studies, quantitative analysis and biostatistics. Students tend to go into the banking and insurance industries, marketing, service companies and research consultancies.
Specificities
One of the strengths of this course is that it is has been designed to develop high level skills in both statistics and economics, thanks to its dual base in the GREMAQ and IMT laboratories.
Teaching is very closely based on real business needs and students are operational immediately. Furthermore, classes in the many available options are taught by business professionals.
Varied partnerships (for teaching, work experience and advice) have been put in place with numerous companies: Inbox, Sanofi-Aventis, Axa, BVA, Ellipsa, Thales and in public sector, with DREAL (Regional Offices for the Environment, Town Planning and Housing), for example.
The ‘Statistic Consultancy’ workshop (business consultancy projects carried out in small groups) helps students get ready to join the world of work
Conditions of admission / Conditions of successful application
ENTRY REQUIREMENTS
A Master 1 in economics and statistics or economics or a Master 1 in applied mathematics.
For overseas students, a BSc, an MA or an MSc obtained from a reputable institution, deemed compatible with the course and approved by the TSE Council. A good command of English is also required.
Prerequisites Subjects to be revised as a matter of priority before the start of the university year are as follows :
Statistics: univariate and bivariate analysis, linear model and Gaussian linear model, regression and factorial plan applications and asymptotic tests (Wald, score and LR).
Data analysis: principal component analysis
Optimisation: Lagrange multipliers
IT: statistical software or spreadsheets
SELECTION CRITERIA
Selection is based on academic excellence and review of the full application by the Admissions Committee.
Program
- Statistics – Fundamentals
1st semester Data Mining (16h + 10h) - Surveys sampling (21h) - Time series (21h) Statistical Software : SAS, R, Python and Excel (33,5h)
2nd semester Big Data (30h) Scoring (30h) Statistical Consulting (30h) Internship
- Statistics – Applications
1st semester -Lifetime data analysis (21h) -Panel data analysis (21h) -Econometrics of qualitative variables(21h) -Econometrics of Marketing (21h) -Non-parametric models (21h) -General linear model (24h)
2nd semester Complex Structure Data Analysis (21h) - Spatial econometrics (21h) - Geomarketing (21h) - Data bases (21h) - Web Mining (21h)
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