Probability theory and Statistics

Lecturer(s): Marie-Christophette BLANCHET, Céline HARTWEG-HELBERT
Course ⋅ 14 hTC ⋅ 16 h


This first part of the course deals with the modelling with random variables. We introduce the notion of density. Some methods of probability calculus, approximations and asymptotic theorems are studied. A important part of the course is devoted to the numerical simulation with MATLAB. The second part of the course deals with statistics. The notions of estimators and tests are introduced. A chapter is devoted to linear regression.

Palabras clave

Probability law, random variables, gaussian vectors, Monte-Carlo method, estimators, biais, statistic tests, linear regression.


Probability : (1) Random Variables (2) Mean and variance (3) Random vectors (4) Random variables sequences- Asymptotic results- Monte-Carlo method.

Statistic : (5) Estimation (6) Estimation by confidence intervalle (7) Statistic tests(8) Linear regression

Learning Outcomes

  • Be able to compute probabilities.
  • Be able to simulate random varaibles with Matlab
  • Be able to estimate some parametres of law from data.
  • Be able to construct and analyse a linear regression.


Final mark = 75% Knowledge + 25% Know-how Knowledge mark = 100% final exam Know-how mark = 100% continuous assessment