Statistical Methods for Data Analysis in Particle Physics

✍ Scribed by Luca Lista (auth.)

• Publisher: Springer International Publishing
• Year: 2016
• Tongue: English
• Leaves: 188
• Series: Lecture Notes in Physics 909
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xix
Probability Theory....Pages 1-19
Probability Distribution Functions....Pages 21-51
Bayesian Approach to Probability....Pages 53-68
Random Numbers and Monte Carlo Methods....Pages 69-80
Parameter Estimate....Pages 81-111
Confidence Intervals....Pages 113-121
Hypothesis Tests....Pages 123-136
Upper Limits....Pages 137-172

✦ Subjects

Elementary Particles, Quantum Field Theory; Measurement Science and Instrumentation; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences