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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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)
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
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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