Data Analysis Techniques for Physical Scientists
Cambridge University Press, 10/5/2017
EAN 9781108416788, ISBN10: 1108416780
Hardcover, 716 pages, 25.4 x 19.3 x 3.6 cm
Language: English
A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.
Preface
How to read this book
1. The scientific method
Part I. Foundation in Probability and Statistics
2. Probability
3. Probability models
4. Classical inference I
estimators
5. Classical inference II
optimization
6. Classical inference III
confidence intervals and statistical tests
7. Bayesian inference
Part II. Measurement Techniques
8. Basic measurements
9. Event reconstruction
10. Correlation functions
11. The multiple facets of correlation functions
12. Data correction methods
Part III. Simulation Techniques
13. Monte Carlo methods
14. Collision and detector modeling
List of references
Index.