Terascale Statistics School 2026

23 Feb 2026, 00:30 → 27 Feb 2026, 14:00 Europe/Berlin

Seminarraum 4a/b (DESY Hamburg)

Andreas Hinzmann (DESY (Deutsches Elektronen Synchrotron)), Dirk Kruecker (CMS (CMS Fachgruppe Searches)), Isabell Melzer-Pellmann (Deutsches Elektronen-Synchrotron DESY), Olaf Behnke (CMS (CMS Fachgruppe TOP))

DESY Terascale Statistics School — Upcoming Edition

The next edition of the DESY Terascale Statistics School will provide an introduction to key statistical methods used in particle-physics data analysis. The school is aimed primarily at PhD students working on LHC or other HEP experiments, but is also open to interested Master’s students and post-doctoral researchers.

Core topics:

•  Basics
•  Hypothesis testing
•  Parameter estimation
•  Confidence intervals
•  Systematic uncertainties
•  Machine learning
•  Unfolding

Invited lecturers (confirmed so far):

• Roger Barlow
• Glen Cowan
• Stephen Jiggins
• Lydia Brenner

(Additional lectures and lecturers will be announced as the program is finalized.) The program will consist mainly of lectures, supplemented by Python-based hands-on exercises. Technical details will be shared ahead of time.

Tentative session scheme:

Fee: 100 Euro (includes conference dinner and coffee breaks)

Accommodation: Please book the DESY Hostel independently (limited availability). 

Note: Participants should bring their own laptops for the hands-on sessions.

Organizing Committee:
I. Henning, A. Hinzmann, D. Kruecker, I. Melzer-Pellmann, O. Behnke

 

 

 

Monday 23 February

1 Registration

2 Opening (Welcome)

Speakers: Andreas Hinzmann (CMS (CMS Fachgruppe Searches)), Olaf Behnke (CMS (CMS Fachgruppe TOP))

:: Afternoon Session

3 Basics: Probabilities, fundamental distributions, Central Limit Theorem etc. (Lecture)

Speaker: Roger Barlow (Huddersfield)

15:30 Coffee Break

4 Hypothesis Testing - Intro (Lecture + Tutorial)

Speaker: Glen Cowan (RHUL)

Tuesday 24 February

:: Morning session

5 Parameter Estimation (Lecture)

Speaker: Roger Barlow (Huddersfield)

10:30 Coffee Break

6 Parameter Estimation (Tutorial)

Speaker: Glen Cowan (RHUL)

12:30 Lunch Break

:: Afternoon session

7 Hypothesis Testing - Limit Setting (Lecture + Tutorial)

Speaker: Glen Cowan (RHUL)

15:30 Coffee break

8 Hypothesis Testing - Limit Setting (Lecture + Tutorial)

Speaker: Glen Cowan (RHUL)

Wednesday 25 February

:: Morning Session

9 Bayesian Parameter Estimation (Lecture + Tutorial)

Speaker: Glen Cowan (RHUL)

10:30 Coffee Break

10 Systematic Uncertainties (Lecture)

Speaker: Roger Barlow (Huddersfield)

12:30 Lunch Break

:: Afternoon Session

11 Errors on Errors (Lecture + Tutorial)

Speaker: Glen Cowan (RHUL)

15:30 Coffee Break

12 To be decided end of January: Either overflow session for Glen Cowan's Tutorials or first lecture slot on Machine Learning, by Stephen Jiggins

Speaker: Glen Cowan (RHUL)

18:30 School Dinner

Thursday 26 February

:: Morning Session

13 Machine Learning I (Lecture + Tutorial)

Speaker: Stephen Jiggins (ATLAS (ATLAS-Experiment))

10:30 Coffee Break

14 Machine Learning II (Lecture + Tutorial)

Speaker: Stephen Jiggins (ATLAS (ATLAS-Experiment))

12:30 Lunch Break

:: Afternoon Session

15 Unfolding I (Lecture + Tutorial)

Speakers: Lydia Brenner (DESY), Lydia Brenner (Nikhef)

15:30 Coffee Break

16 Unfolding II (Lecture + Tutorial)

Speakers: Lydia Brenner (DESY), Lydia Brenner (Nikhef)

Friday 27 February

:: Morning Session and closing

17 Machine Learning III (Lecture + Tutorial)

Speaker: Stephen Jiggins (ATLAS (ATLAS-Experiment))

10:30 Coffee Break

18 Machine Learning IV (Lecture + Turorial)

Speaker: Stephen Jiggins (ATLAS (ATLAS-Experiment))

19 Closing of the School

Speakers: Andreas Hinzmann (CMS (CMS Fachgruppe Searches)), Olaf Behnke (CMS (CMS Fachgruppe TOP))