Probability And Statistics For Physical Sciences
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Probability And Statistics For Physical Sciences
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Author : Brian Martin
language : en
Publisher: Elsevier
Release Date : 2023-09-05
Probability And Statistics For Physical Sciences written by Brian Martin and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-05 with Mathematics categories.
Probability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical sciences. This brief yet systematic introduction explains the origin of key techniques, providing mathematical background and useful formulas. The text does not assume any background in statistics and is appropriate for a wide-variety of readers, from first-year undergraduate students to working scientists across many disciplines. - Provides a collection of useful formulas with mathematical background - Includes worked examples throughout and end-of-chapter problems for practice - Offers a logical progression through topics and methods in statistics and probability
Probability And Statistics In The Physical Sciences
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Author : Byron P. Roe
language : en
Publisher: Springer Nature
Release Date : 2020-09-26
Probability And Statistics In The Physical Sciences written by Byron P. Roe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-26 with Science categories.
This book, now in its third edition, offers a practical guide to the use of probability and statistics in experimental physics that is of value for both advanced undergraduates and graduate students. Focusing on applications and theorems and techniques actually used in experimental research, it includes worked problems with solutions, as well as homework exercises to aid understanding. Suitable for readers with no prior knowledge of statistical techniques, the book comprehensively discusses the topic and features a number of interesting and amusing applications that are often neglected. Providing an introduction to neural net techniques that encompasses deep learning, adversarial neural networks, and boosted decision trees, this new edition includes updated chapters with, for example, additions relating to generating and characteristic functions, Bayes’ theorem, the Feldman-Cousins method, Lagrange multipliers for constraints, estimation of likelihood ratios, and unfolding problems.
Probability And Statistics For The Engineering Computing And Physical Sciences
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Author : Edward R. Dougherty
language : en
Publisher:
Release Date : 1990
Probability And Statistics For The Engineering Computing And Physical Sciences written by Edward R. Dougherty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Probabilities categories.
E T Jaynes Papers On Probability Statistics And Statistical Physics
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Author : R.D. Rosenkrantz
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
E T Jaynes Papers On Probability Statistics And Statistical Physics written by R.D. Rosenkrantz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le. , as distributions that are most non-committal with regard to missing information among all those satisfying the macroscopically given constraints). There is then no need to make additional assumptions of ergodicity or metric transitivity; the theory proceeds entirely by inference from macroscopic measurements and the underlying dynamical assumptions. Moreover, the method of maximizing the entropy is completely general and applies, in particular, to irreversible processes as well as to reversible ones. The next three chapters provide a broader framework - at once Bayesian and objective - for maximum entropy inference. The basic principles of inference, including the usual axioms of probability, are seen to rest on nothing more than requirements of consistency, above all, the requirement that in two problems where we have the same information we must assign the same probabilities. Thus, statistical mechanics is viewed as a branch of a general theory of inference, and the latter as an extension of the ordinary logic of consistency. Those who are familiar with the literature of statistics and statistical mechanics will recognize in both of these steps a genuine 'scientific revolution' - a complete reversal of earlier conceptions - and one of no small significance.
Probability And Statistics For Physical Sciences
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Author : Brian Martin
language : en
Publisher: Academic Press
Release Date : 2023-11-01
Probability And Statistics For Physical Sciences written by Brian Martin and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-01 with Mathematics categories.
Probability and Statistics for Physical Sciences, Second Edition, is an accessible guide to commonly used concepts and methods in statistical analysis, as used in physical sciences. This brief yet systematic introduction explains the origin of key techniques, providing mathematical background and useful formulas. The text does not assume any background in statistics and is appropriate for a wide-variety of readers, from first year undergraduate students to working scientists across many disciplines.
Statistical Methods For Physical Science
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Author :
language : en
Publisher: Academic Press
Release Date : 1994-12-13
Statistical Methods For Physical Science written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-12-13 with Science categories.
This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics. The scope of topics covered is wide-ranging-the text discusses a variety of the most commonly used classical methods and addresses newer methods that are applicable or potentially important. The chapter authors motivate readers with their insightful discussions. - Examines basic probability, including coverage of standard distributions, time series models, and Monte Carlo methods - Describes statistical methods, including basic inference, goodness of fit, maximum likelihood, and least squares - Addresses time series analysis, including filtering and spectral analysis - Includes simulations of physical experiments - Features applications of statistics to atmospheric physics and radio astronomy - Covers the increasingly important area of modern statistical computing
Probability And Statistics In The Physical Sciences
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Author : Byron P. Roe
language : en
Publisher:
Release Date : 2020
Probability And Statistics In The Physical Sciences written by Byron P. Roe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Mathematical physics categories.
This book, now in its third edition, offers a practical guide to the use of probability and statistics in experimental physics that is of value for both advanced undergraduates and graduate students. Focusing on applications and theorems and techniques actually used in experimental research, it includes worked problems with solutions, as well as homework exercises to aid understanding. Suitable for readers with no prior knowledge of statistical techniques, the book comprehensively discusses the topic and features a number of interesting and amusing applications that are often neglected. Providing an introduction to neural net techniques that encompasses deep learning, adversarial neural networks, and boosted decision trees, this new edition includes updated chapters with, for example, additions relating to generating and characteristic functions, Bayes' theorem, the Feldman-Cousins method, Lagrange multipliers for constraints, estimation of likelihood ratios, and unfolding problems.
Probability And Related Topics In Physical Sciences
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Author : Mark Kac
language : en
Publisher: American Mathematical Soc.
Release Date : 1959-12-31
Probability And Related Topics In Physical Sciences written by Mark Kac and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1959-12-31 with Mathematics categories.
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Data Analysis For Physical Scientists
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Author : Les Kirkup
language : en
Publisher: Cambridge University Press
Release Date : 2012-02-16
Data Analysis For Physical Scientists written by Les Kirkup and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-16 with Computers categories.
Introducing data analysis techniques to help undergraduate students develop the tools necessary for studying and working in the physical sciences.
Bayesian Logical Data Analysis For The Physical Sciences
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Author : Phil Gregory
language : en
Publisher: Cambridge University Press
Release Date : 2005-04-14
Bayesian Logical Data Analysis For The Physical Sciences written by Phil Gregory and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-14 with Mathematics categories.
Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.