Ebook: Statistical Methods for Data Analysis in Particle Physics
Author: Luca Lista
- Genre: Physics // Quantum Physics
- Tags: Elementary Particles Quantum Field Theory, Measurement Science and Instrumentation, Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences
- Series: Lecture Notes in Physics 909
- Year: 2015
- Publisher: Springer
- Edition: 2016
- Language: English
- pdf
Self-contained course-based graduate text
Contains many exercices and worked examples
Authored by an expert in the field
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.
Topics
Elementary Particles, Quantum Field Theory
Measurement Science, Instrumentation
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Contains many exercices and worked examples
Authored by an expert in the field
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.
Topics
Elementary Particles, Quantum Field Theory
Measurement Science, Instrumentation
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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