Terascale Statistics School 2025

Contribution List

1. Registration

24/02/2025, 12:30

2. Welcome

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

24/02/2025, 13:15

3. Basics (Probabilities, Distributions, CLT)

Roger Barlow (Huddersfield)

24/02/2025, 13:20

Lectures + Discussions

5. Hypothesis Testing - basics

Glen Cowan (RHUL)

24/02/2025, 15:30

Lecture + Discussion

49. Hypothesis testing - Tutorial

Glen Cowan (RHUL)

24/02/2025, 16:30

Tutorial:
Link to files: https://www.pp.rhul.ac.uk/~cowan/stat/exercises/

Description/Tasksheet (file is also attached):
https://www.pp.rhul.ac.uk/~cowan/stat/exercises/cowan_stat_exercises.pdf
Today: Exercises on hypothesis testing 1a-1g, see p.32 ff

6. Parameter Estimation

Roger Barlow (Huddersfield)

25/02/2025, 09:00

Lectures + Discussion

7. Parameter Estimation - Tutorial

Glen Cowan (RHUL)

25/02/2025, 10:30

Tutorial - Introduction to the Python code and practical exercises with it

https://www.pp.rhul.ac.uk/~cowan/stat/exercises/cowan_stat_exercises.pdf
Today: p4 ff
Tutorial 1: Maximum Likelihood Fitting

8. Hypothesis Testing - Limit Setting

Glen Cowan (RHUL)

25/02/2025, 14:00

Lectures + Discussions

9. Systematics

Roger Barlow (Huddersfield)

25/02/2025, 16:00

Lectures + Discussions

10. Bayesian Parameter Estimation - Intro + Tutorial

Glen Cowan (RHUL)

26/02/2025, 09:00

Tutorial + introductory Lecture

11. Systematics: Errors on Errors

Glen Cowan (RHUL)

26/02/2025, 11:00

Lecture + Discussion + Tutorial
Solutions are at https://www.pp.rhul.ac.uk/~cowan/stat/exercises_full/

12. Machine Learning I

Tilman Plehn (Heidelberg University), Tilman Plehn (Heidelberg University)

26/02/2025, 14:00

Lectures + Discussions
https://www.thphys.uni-heidelberg.de/~plehn/pics/modern_ml.pdf
https://github.com/heidelberg-hepml/ml-tutorials

25. Disasters in Statistical Inference in Particle Physics

Roger Barlow (Huddersfield)

26/02/2025, 16:30

Lecture + Discussion

14. Machine Learning II

Tilman Plehn (Heidelberg University), Tilman Plehn (Heidelberg University)

27/02/2025, 09:00

Lectures + Discussions

15. Theory Uncertainties

Frank Tackmann (T (Phenomenology))

27/02/2025, 11:00

Lectures + Discussion

30. Unfolding

Lydia Brenner (Nikhef)

27/02/2025, 14:00

Lectures + Discussion

33. Asymmetric uncertainties

Roger Barlow (Huddersfield)

27/02/2025, 16:30

Lectures + Discussion

35. Machine Learning III

Tilman Plehn (Heidelberg University), Tilman Plehn (Heidelberg University)

28/02/2025, 09:00

Lectures + Discussion

37. Modern Bayesian inference in practice

Kevin Kröninger (TU Dortmund)

28/02/2025, 11:15

Lectures + Discussion

39. Closing of school

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

28/02/2025, 12:15

4. Basics II (Probabilities, distributions, CLT)

Roger Barlow (Huddersfield)

16. Discussion time

19. Discussion time

21. Discussion time

22. Discussion time

27. Discussion time

29. Discussion time

31. Discussion time

34. Discussion time

36. Discussion time

38. Discussion time

40. Discussion time

41. Discussion time

44. Discussion time

46. Discussion time

48. Discussion time

13. Errors on Errors

Glen Cowan (RHUL)

A statistical model is presented where the uncertainty in assignment of systematic errors is taken into account. Estimates of the systematic variances are modeled as gamma distributed variables. The resulting confidence intervals show interesting and useful properties, e.g., when averaging measurements to estimate their mean, the size of the confidence interval increases as a for decreasing...

20. Extra time for discussion

17. Hypothesis Testing II

Glen Cowan (RHUL)

18. Interactive Session (exercises/tutorials)

23. Interactive Session (exercises/tutorials)

43. Overflow time

45. Overflow time

47. Overflow time

42. Setting up of computer interactive exercises

28. Theory uncertainties II

Frank Tackmann (T (Phenomenology))

24. Time for discussion

26. Time for discussion

32. Unfolding II

Lydia Brenner (Nikhef)