May 7 – 11, 2017
Hotel Continental Terme, Ischia
Europe/Rome timezone

Scientific Program

Probability theory

  • Introduction to probability theory
  • Bayesian and frequentist approaches to probability
  • Random variables, distributions and main properties

Statistical inference

  • Parameter estimates, properties of estimators
  • Maximum likelihood method
  • Pearson and Neyman chi-squares

Hypothesis testing and interval estimation

  • Hypothesis testing
  • Goodness of fit
  • Frequentist and Bayesian upper limits

Multivariate analysis

  • Complex network analysis
  • Multivariate discrimination methods
  • Boosted decision trees
  • Artificial neural networks
  • Deep Learning

Statistical software tools

  • Overview of the main statistical tools
  • RooFit, RooStats
  • Usage examples and code demonstrations

Confirmed lecturers:

  • Roger Barlow (Univ. of Huddersfield)
  • Olaf Behnke (DESY, Germany)
  • Glen Cowan (Royal Holloway, London)
  • Ilya Narsky (MathWorks, USA)
  • Mario Pelliccioni (INFN Torino)
  • Antonio Scala (CNR, Rome)
  • Andrey Ustyuzhanin (Yandex, Russia)