INFN School of Statistics 2019

2 Jun 2019, 08:30 → 7 Jun 2019, 15:00 Europe/Rome

Hotel Ariston, Paestum

The INFN School Of Statistics intends to provide an overview of statistical methods and tools used in particle, astro-particle and nuclear physics.
This School is targeted towards physicists interested in data analysis ranging from PhD students to senior physicists willing to extend their knowledge and skills in the field of statistical methods. The School takes place in Paestum (Salerno, Italy) from 3rd to 7th of June 2019.
Lectures are subdivided into five sections: the first section will be an introduction to probability theory, including fundamental definitions of frequentist and Bayesian approaches to probability. The second section is devoted to statistical methods, including parameter estimates, maximum likelihood and chi-squared methods. The third section will provide an overview of statistical methods adopted to define confidence intervals and upper limits. The fourth section will cover multivariate techniques, including artificial neural networks and boosted decision trees. Finally, the fifth section will present the state-of-the-art software tools used for statistical evaluations with interactive exercises.

Registration will open early in 2022.

The programme and timetable my be subject to changes before registration opens.

For further information, please contact infnstat2019@na.infn.it.

Previous editions:

• INFN School of Statistics 2017
• INFN School of Statistics 2015
• INFN School of Statistics 2013

 

This school is co-funded by INFN, INFN - Sezione di Napoli, University "Federico II", Naples, and by the Department of Physics of University "Federico II", Naples.

 

This school is part of the training programme of the Insights Innovative Training Network, funded by the European Union's Horizon 2020 research and innovation programme, call H2020-MSCA-ITN-2017, under Grant Agreement n. 765710.

We thank the Archeological Park of Paestum for the support offered to this school.

 

 

 

 

 

 

 

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computer-instructions.html

group-photo.jpg

poster.pdf

Sunday, 2 June

19:00 Registration

20:00 Dinner

Monday, 3 June

08:15 Registration

1 Welcome

Speaker: Prof. Luca Lista (Università degli Studi di Napoli Federico II)

INFNStat2019.pdf

2 Lecture 1.1: Probability theory

Speaker: Harrison Prosper (Florida State University, Tallahassee )

INFN_SOS2019_Prosper01.pdf

10:30 Coffe break

3 Lecture 1.2: Probability theory

Speaker: Harrison Prosper (Florida State University, Tallahassee )

cauchy.ipynb

INFN_SOS2019_Prosper02.pdf

least_squares_fit.ipynb

least_squares_with_roofit.ipynb

models.cc

12:30 Lunch

4 Lecture 2.1: Parameter estimation

Speaker: Glen Cowan (Royal Holloway, University of London )

cowan_paestum_2019.pdf

15:30 Coffe break

5 Lecture 3.1: Hypothesis testing and interval estimation

Speaker: Eilam Gross (Weizmann Institute of Science )

ht_part1.pdf

20:00 Dinner

Tuesday, 4 June

6 Lecture 2.2: Parameter estimation

Speaker: Glen Cowan (Royal Holloway, University of London )

10:30 Coffe break

7 Lecture 3.2: Hypothesis testing and interval estimation

Speaker: Eilam Gross (Weizmann Institute of Science )

ht_part2.pdf

12:30 Lunch

8 Lecture 3.3: Hypothesis testing and interval estimation

Speaker: Eilam Gross (Weizmann Institute of Science )

lee.pdf

15:30 Coffe break

9 Lecture 4.1: Statistical software I - hands-on session

Speaker: Mario Pelliccioni (TO)

INFNStat_2019.pdf

Twiki

20:00 Dinner

Wednesday, 5 June

10 Lecture 4.2: Statistical software I - hands-on session

Speaker: Mario Pelliccioni (TO)

10:30 Coffe break

11 Lecture 4.3: Statistical software I - hands-on session

Speaker: Mario Pelliccioni (TO)

12:30 Lunch

14:00 Excursion

20:30 Dinner

Thursday, 6 June

12 Lecture 5.1: Multivariate analysis

Speaker: Aldo Solari (University of Milano-Bicocca)

aldo-solari-1.pdf

10:30 Coffe break

13 Lecture 5.2: Multivariate analysis

Speaker: Aldo Solari (University of Milano-Bicocca)

aldo-solari-2.pdf

12:30 Lunch

14 Lecture 6.1: Machine learning

Speaker: Sergei Gleyzer (University of Florida )

ml-1.pdf

15:30 Coffe break

15 Lecture 7.1: Machine learning hackathon

Speaker: Sergei Gleyzer (University of Florida )

Github LHC hackathon

Higgs data set

Higgs detalied paper

Jupyter Hub

ML hackaton e-mail

Slack channel

20:00 Dinner

Friday, 7 June

16 Lecture 6.2: Machine learning

Speaker: Sergei Gleyzer (University of Florida )

10:30 Coffe break

17 Lecture 7.2: Machine learning hackathon

Speaker: Sergei Gleyzer (University of Florida )

12:30 Departure