Data analysis and modelisation

  • Cours (CM) 20h
  • Cours intégrés (CI) -
  • Travaux dirigés (TD) -
  • Travaux pratiques (TP) -
  • Travail étudiant (TE) -

Langue de l'enseignement : Anglais

Niveau de l'enseignement : B2-Avancé - Utilisateur indépendant

Description du contenu de l'enseignement

Data analysis and modelisation
  • Basic concepts :
    • Definition of statistical and systematical uncertainties on measurements.
    • Random variables, probabilities, momenta and probabilistic laws.
    • Three basic laws of random variables, the normal law and the central limit theorem.
    • Application : counting rates, selection efficiency, estimation for means.
  • Combining uncertainties from measurements :
    • Joint probabilistic laws, covariance, correlation, the two-gaussians cases.
    • Uncertainty propagation.
    • Application : combining measurements of the same quantity and some practical examples.
  • Parameter estimation :
    • Introduction to statistics.
    • Basic methods : maximum likelihood (the gaussian case, uncertainties, binned likelihood, extended likelihood), least squares (linear case, uncertainties, chi2 law).
    • Minimizing methods.
  • Hypothesis testing :
    • Histogram fits.
    • Tests : two and single hypothesis, power and error, p-value, the Neyman test, chi2-test , Kolmogorov-test.
    • Application : histogram comparison, Higgs search at LEP.
  • Advanced estimation :
    • Interval estimation (confidence levels and intervals), low statistics, nuisance parameters.
    • Dynamic estimation, Kalman filter.
    • Application : discovery limits.
  • Modelization :
    • Random number generation, Monte-Carlo techniques.
    • Application to simulation, use cases with ROOT.
  • Advanced techniques :
    • principle analysis components (PCA) for complex ensemble.
    • Multivariate Analysis (MVA), Fisher discriminants, artificial neural networks, decision trees.

Contact

Faculté de physique et ingénierie

3-5, rue de l'Université
67084 STRASBOURG CEDEX

Formulaire de contact

Responsable