Goals

The objective of the course is to introduce the main elements of the theory of linear and non-linear regression. 

Content

The main concepts studied are as follows: Normal, Chi-square, Student and Fisher-Snedecor distributions (as well as the relationships between them), random vectors and more particularly Gaussian random vectors, simple linear regression, multiple linear regression, multicollinearity, diagnostics, choice of linear model and non-linear regression.

Teaching methods

13 lectures ex-cathedra. The slides are available on webcampus.
 
The exercise sessions will be mainly oriented towards the statistical software R and the application of regression methods to real data sets.

Assessment method

Two-part evaluation:
 
1) A written exam which will be mainly oriented towards the understanding of the statistical theory.
 
2) Four projects throughout the semester which will consist of the analysis of real data sets, and which will include the following stages: modeling, estimation of model parameters, selection of variables, examination of the validity of the chosen model. The projects will be evaluated on the basis of written reports.

Language of instruction

French
Training Study programme Block Credits Mandatory
Bachelor in Mathematics Standard 0 5
Bachelor in Mathematics Standard 3 5