January 21, 2021

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Statistics for Physical Sciences

Statistics for Physical Sciences
Author : Brian Martin
Publisher : Academic Press
Release Date : 2012-01-25
Category : Mathematics
Total pages :320
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Statistics for Physical Sciences is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origins. It steers a path between the extremes of a recipe of methods with a collection of useful formulas, and a full mathematical account of statistics, while at the same time developing the subject in a logical way. The book can be read in its entirety by anyone with a basic exposure to mathematics at the level of a first-year undergraduate student of physical science and should be useful for practising physical scientists, plus undergraduate and postgraduate students in these fields. Offers problems at the end of each chapter Features worked examples across all of the chapters Provides a collection of useful formulas in order to give a detailed account of mathematical statistics

Statistical Data Analysis for the Physical Sciences

Statistical Data Analysis for the Physical Sciences
Author : Adrian Bevan
Publisher : Cambridge University Press
Release Date : 2013-05-09
Category : Science
Total pages :129
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Data analysis lies at the heart of every experimental science. Providing a modern introduction to statistics, this book is ideal for undergraduates in physics. It introduces the necessary tools required to analyse data from experiments across a range of areas, making it a valuable resource for students. In addition to covering the basic topics, the book also takes in advanced and modern subjects, such as neural networks, decision trees, fitting techniques and issues concerning limit or interval setting. Worked examples and case studies illustrate the techniques presented, and end-of-chapter exercises help test the reader's understanding of the material.

Statistical Methods for Physical Science

Statistical Methods for Physical Science
Author : Anonim
Publisher : Academic Press
Release Date : 1994-12-13
Category : Science
Total pages :542
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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

Bayesian Logical Data Analysis for the Physical Sciences

Bayesian Logical Data Analysis for the Physical Sciences
Author : Phil Gregory
Publisher : Cambridge University Press
Release Date : 2005-04-14
Category : Mathematics
Total pages :129
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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.

Probability and Statistics for the Engineering, Computing, and Physical Sciences

Probability and Statistics for the Engineering, Computing, and Physical Sciences
Author : Edward R. Dougherty
Publisher : Unknown
Release Date : 1990
Category : Mathematics
Total pages :800
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Generalized Hypergeometric Functions with Applications in Statistics and Physical Sciences

Generalized Hypergeometric Functions with Applications in Statistics and Physical Sciences
Author : A. M. Mathai,R. K. Saxena
Publisher : Springer
Release Date : 2006-11-15
Category : Mathematics
Total pages :318
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Statistics

Statistics
Author : R. J. Barlow
Publisher : John Wiley & Sons
Release Date : 2013-06-05
Category : Science
Total pages :224
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The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition F. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A.C. Phillips Computing for Scientists R. J. Barlow and A. R. Barnett Written by a physicist, Statistics is tailored to the needs of physical scientists, containing and explaining all they need to know. It concentrates on parameter estimation, especially the methods of Least Squares and Maximum Likelihood, but other techniques, such as hypothesis testing, Bayesian statistics and non-parametric methods are also included. Intended for reasonably numerate scientists it contains all the basic formulae, their derivations and applications, together with some more advanced ones. Statistics features: * Comprehensive coverage of the essential techniques physical scientists are likely to need. * A wealth of examples, and problems with their answers. * Flexible structure and organisation allows it to be used as a course text and a reference. * A review of the basics, so that little prior knowledge is required.

Data Analysis Techniques for Physical Scientists

Data Analysis Techniques for Physical Scientists
Author : Claude Pruneau
Publisher : Cambridge University Press
Release Date : 2017-09-30
Category : Science
Total pages :129
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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.

A Practical Guide to Data Analysis for Physical Science Students

A Practical Guide to Data Analysis for Physical Science Students
Author : Louis Lyons,Lyons Louis
Publisher : Cambridge University Press
Release Date : 1991-11-29
Category : Science
Total pages :95
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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 analyze 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. 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.

Bayesian Methods for the Physical Sciences

Bayesian Methods for the Physical Sciences
Author : Stefano Andreon,Brian Weaver
Publisher : Springer
Release Date : 2015-05-19
Category : Mathematics
Total pages :238
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Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University

Probability and Statistics in the Physical Sciences

Probability and Statistics in the Physical Sciences
Author : Byron P. Roe
Publisher : Springer Nature
Release Date : 2021
Category :
Total pages :129
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Statistics and Analysis of Scientific Data

Statistics and Analysis of Scientific Data
Author : Massimiliano Bonamente
Publisher : Springer
Release Date : 2016-11-08
Category : Science
Total pages :318
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The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text. • end-of-chapter summary boxes, for easy reference. As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.

Statistical Data Analysis

Statistical Data Analysis
Author : Glen Cowan
Publisher : Oxford University Press
Release Date : 1998
Category : Mathematics
Total pages :197
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This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are taken from particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques, statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).

Data Reduction and Error Analysis for the Physical Sciences

Data Reduction and Error Analysis for the Physical Sciences
Author : Philip R. Bevington,D. Keith Robinson
Publisher : McGraw-Hill Science, Engineering & Mathematics
Release Date : 1992
Category : Mathematics
Total pages :328
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This book is designed as a laboratory companion, student textbook or reference book for professional scientists. The text is for use in one-term numerical analysis, data and error analysis, or computer methods courses, or for laboratory use. It is for the sophomore-junior level, and calculus is a prerequisite. The new edition includes applications for PC use.

A Handbook of Generalized Special Functions for Statistical and Physical Sciences

A Handbook of Generalized Special Functions for Statistical and Physical Sciences
Author : A. M. Mathai,Professor of Mathematics and Statistics A M Mathai
Publisher : Oxford University Press, USA
Release Date : 1993
Category : Philosophy
Total pages :235
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Complicated generalized special functions such as Meijer's G-functions and functions of matrix arguments are here presented at a level suitable for every potential user. This handbook is thus a valuable reference source and a manual for researchers and advanced students in mathematical statistics, mathematical physics, several branches of mathematics, engineering problems, econometrics, and various applied areas where transcendental functions are used.