TL;DR
This paper emphasizes the importance of rigorous statistical analysis in high energy physics to maximize data insights, discussing practical issues encountered in typical analyses.
Contribution
It provides practical guidance on statistical methods tailored for high energy physics data analysis, addressing common challenges and solutions.
Findings
Highlights key statistical challenges in HEP analyses
Provides practical solutions for data interpretation
Enhances reliability of experimental conclusions
Abstract
Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical analysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParticle Detector Development and Performance