Probability theory
- Introduction to probability theory
- Distribution functions of random variables
- Conditional probability, Bayes theorem
- Exercise session
Statistical inference
- Parameter estimates, properties of estimators
- Maximum likelihood method
- Pearson and Neyman chi-squares
Hypothesis testing and interval estimation
- Hypothesis tests
- Upper limits and significance evaluation
- Treatment of nuisance parameters
- Goodness of fit
- Exercise session
Seminar
- Experience with statistical analysis of covid data
Statistical software tools
- Overview of the main statistical tools
- RooFit, RooStats
- Hands-on exercises
Multivariate analysis
- Introduction to multivariate analysis
- Supervised learning: classification and regression
- Unsupervised learning, etc.
- Hands-on tutorial
Lecturers:
- Sara Algeri, University of Minnesota
- Glen Cowan, Royal Holloway University of London
- Michael A. Kagan, SLAC, Standord
- Jennifer Ngadiuba, Fermilab
- Mario Pelliccioni, INFN - Torino
- Harrison Prosper, Florida State University
- Gaetano Salina (COVID seminar), INFN - Roma Tor Vergata
