Sinossi
This book is intended as a practical guide for advanced undergraduates to the use of probability and statistics in experimental physics. The emphasis is on applications and understanding, on techniques that are used in experimental physics, and on the use of computers. This second edition includes a new chapter on queuing problems (such as, how large a buffer does one need deal with a random stream of data), and it introduces a new method for dealing with experiments in which only a few events are observed.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Recensione
From the reviews of the second edition:
"This book is the second edition ... of a practical introduction into probability and statistics in experimental physics. The book is primarily written for undergraduate and graduate students and contains a new chapter on queueing theory and an additional discussion of the Feldman-Cousins unified method for estimating confidence intervals." (Ulrich Horst, Zentralblatt MATH, Vol. 1011, 2003)
"The book under review is rather unconventional in many respects, in particular concerning the choice of covered topics and the style of presentation. ... Its main goal is to provide the reader with techniques actually used in experimental research. They are illustrated by a series of worked problems. ... some material is included that one hardly finds in other books of this kind, like elements of queuing theory ... . many experimental physicists would appreciate probably to have a copy of this book within hand-reach." (F. Binon, Physicalia, Vol. 38 (5), 2002)
Contenuti
Preface. 1 Basic Probability Concepts. 2 Some Initial Definitions. 3 Some Results of Specific Distributions. 4 Discrete Distributions and Combinatorials,5.Specific Discrete Distributions. 6 The Normal (or Gaussian) Distribution and Other Continuous Distributions. 7 Generating Functions and Characteristic Functions. 8 The Monte Carlo Method: Computer Simulation of Experiments. 9 Queueing Theory and Other Probability Questions. 10 Two Dimensional and Multi-Dimensional Distributions.,11.The Central Limit Theorem. 12 Inverse Probability; Confidence Limits. 13 Methods for Estimating Parameters. Least Squares and Maximum Likelihood. 14 Curve Fitting. 15 Bartlett S Function; Estimating Likelihood Ratios Needed for an Experiment. 16 Interpolating Functions and Unfolding Problems. 17 Fitting Data with Correlations and Constraints. 18 Beyond Maximum Likelihood and Least Squares; Robust Methods,References
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intended for advanced undergraduates and graduate students, this book is a practical guide to the use of probability and statistics in experimental physics. The emphasis is on applications and understanding, on theorems and techniques actually used in research. The text is not a comprehensive text in probability and statistics; proofs are sometimes omitted if they do not contribute to intuition in understanding the theorem. The problems, some with worked solutions, introduce the student to the use of computers; occasional reference is made to routines available in the CERN library, but other systems, such as Maple, can also be used. Topics covered include: basic concepts; definitions; some simple results independent of specific distributions; discrete distributions; the normal and other continuous distributions; generating and characteristic functions; the Monte Carlo method and computer simulations; multi-dimensional distributions; the central limit theorem; inverse probability and confidence belts; estimation methods; curve fitting and likelihood ratios; interpolating functions; fitting data with constraints; robust estimation methods. This second edition introduces a new method for dealing with small samples, such as may arise in search experiments, when the data are of low probability. It also includes a new chapter on queuing problems (including a simple, but useful buffer length example). In addition new sections discuss over- and under-coverage using confidence belts, the extended maximum-likelihood method, the use of confidence belts for discrete distributions, estimation of correlation coefficients, and the effective variance method for fitting y = f(x) when both x and y have measurement errors.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch. Codice articolo 9781441928955
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Intended for advanced undergraduates and graduate students, this book is a practical guide to the use of probability and statistics in experimental physics. The emphasis is on applications and understanding, on theorems and techniques actually used in research. The text is not a comprehensive text in probability and statistics; proofs are sometimes omitted if they do not contribute to intuition in understanding the theorem. The problems, some with worked solutions, introduce the student to the use of computers; occasional reference is made to routines available in the CERN library, but other systems, such as Maple, can also be used. Topics covered include: basic concepts; definitions; some simple results independent of specific distributions; discrete distributions; the normal and other continuous distributions; generating and characteristic functions; the Monte Carlo method and computer simulations; multi-dimensional distributions; the central limit theorem; inverse probability and confidence belts; estimation methods; curve fitting and likelihood ratios; interpolating functions; fitting data with constraints; robust estimation methods. This second edition introduces a new method for dealing with small samples, such as may arise in search experiments, when the data are of low probability. It also includes a new chapter on queuing problems (including a simple, but useful buffer length example). In addition new sections discuss over- and under-coverage using confidence belts, the extended maximum-likelihood method, the use of confidence belts for discrete distributions, estimation of correlation coefficients, and the effective variance method for fitting y = f(x) when both x and y have measurement errors. Codice articolo 9781441928955
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