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Statistical Data Analysis For The Physical Sciences


Statistical Data Analysis For The Physical Sciences
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Statistical Data Analysis For The Physical Sciences


Statistical Data Analysis For The Physical Sciences
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Author : Adrian Bevan
language : en
Publisher:
Release Date : 2013

Statistical Data Analysis For The Physical Sciences written by Adrian Bevan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Physical sciences categories.


A modern introduction to statistics for undergraduates in physics, with worked examples and case studies to illustrate techniques presented.



Statistical Data Analysis For The Physical Sciences


Statistical Data Analysis For The Physical Sciences
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Author : Adrian Bevan
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-09

Statistical Data Analysis For The Physical Sciences written by Adrian Bevan 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 2013-05-09 with Science categories.


A modern introduction to statistics for undergraduates in physics, with worked examples and case studies to illustrate techniques presented.



A Practical Guide To Data Analysis For Physical Science Students


A Practical Guide To Data Analysis For Physical Science Students
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Author : Louis Lyons
language : en
Publisher: Cambridge University Press
Release Date : 1991-11-29

A Practical Guide To Data Analysis For Physical Science Students written by Louis Lyons 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 1991-11-29 with Science categories.


It is usually straightforward to calculate the result of a practical experiment in the laboratory. Estimating the accuracy of that result is often regarded by students as an obscure and tedious routine, involving much arithmetic. An estimate of the error is, however, an integral part of the presentation of the results of experiments. This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyse data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics. Specific examples are worked through step by step in the text. Emphasis is placed on the need to think about whether a calculated error is sensible. At first students should take this book with them to the laboratory, and the format is intended to make this convenient. The book will provide the necessary understanding of what is involved, should inspire confidence in the method of estimating errors, and enable numerical calculations without too much effort. The author's aim is to make practical classes more enjoyable. Students who use this book will be able to complete their calculations quickly and confidently, leaving time to appreciate the basic physical ideas involved in the experiments.



Data Reduction And Error Analysis For The Physical Sciences


Data Reduction And Error Analysis For The Physical Sciences
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Author : Philip Bevington
language : en
Publisher:
Release Date : 2003

Data Reduction And Error Analysis For The Physical Sciences written by Philip Bevington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.


The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation is developed from a practical point of view, including enough derivation to justify the results, but emphasizing methods of handling data more than theory. The text provides a variety of numerical and graphical techniques. Computer programs that support these techniques will be available on an accompanying website in both Fortran and C++.



Probability And Statistics For Physical Sciences


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



Statistics For Physical Sciences


Statistics For Physical Sciences
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Author : Brian Martin
language : en
Publisher: Academic Press
Release Date : 2012-01-19

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 2012-01-19 with Mathematics categories.


"Statistics in physical science is principally concerned with the analysis of numerical data, so in Chapter 1 there is a review of what is meant by an experiment, and how the data that it produces are displayed and characterized by a few simple numbers"--



Bayesian Logical Data Analysis For 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.



Statistical Data Analysis


Statistical Data Analysis
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Author : Glen Cowan
language : en
Publisher:
Release Date : 2023

Statistical Data Analysis written by Glen Cowan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Physical sciences categories.


This is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences.



Data Analysis Techniques For Physical Scientists


Data Analysis Techniques For Physical Scientists
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Author : Claude A. Pruneau
language : en
Publisher: Cambridge University Press
Release Date : 2017-10-05

Data Analysis Techniques For Physical Scientists written by Claude A. Pruneau 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 2017-10-05 with Language Arts & Disciplines categories.


A comprehensive guide to data analysis techniques for the physical sciences including probability, statistics, data reconstruction, data correction and Monte Carlo methods. This book provides a valuable resource for advanced undergraduate and graduate students, as well as practitioners in the fields of experimental particle physics, nuclear physics and astrophysics.



Probability And Statistics In The Physical Sciences


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.