An Introduction to Error Analysis PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download An Introduction to Error Analysis PDF full book. Access full book title An Introduction to Error Analysis by John Robert Taylor. Download full books in PDF and EPUB format.
Author: John Robert Taylor
Publisher: Univ Science Books
ISBN: 9780935702422
Category : Mathematics
Languages : en
Pages : 327
Get Book Here
Book Description
Problems after each chapter
Author: John Robert Taylor
Publisher: Univ Science Books
ISBN: 9780935702422
Category : Mathematics
Languages : en
Pages : 327
Get Book Here
Book Description
Problems after each chapter
Author: Ifan Hughes
Publisher: OUP Oxford
ISBN: 0191576565
Category : Science
Languages : en
Pages : 152
Get Book Here
Book Description
This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.
Author: Robert M. Corless
Publisher: Springer Science & Business Media
ISBN: 1461484537
Category : Mathematics
Languages : en
Pages : 896
Get Book Here
Book Description
This book provides an extensive introduction to numerical computing from the viewpoint of backward error analysis. The intended audience includes students and researchers in science, engineering and mathematics. The approach taken is somewhat informal owing to the wide variety of backgrounds of the readers, but the central ideas of backward error and sensitivity (conditioning) are systematically emphasized. The book is divided into four parts: Part I provides the background preliminaries including floating-point arithmetic, polynomials and computer evaluation of functions; Part II covers numerical linear algebra; Part III covers interpolation, the FFT and quadrature; and Part IV covers numerical solutions of differential equations including initial-value problems, boundary-value problems, delay differential equations and a brief chapter on partial differential equations. The book contains detailed illustrations, chapter summaries and a variety of exercises as well some Matlab codes provided online as supplementary material. “I really like the focus on backward error analysis and condition. This is novel in a textbook and a practical approach that will bring welcome attention." Lawrence F. Shampine A Graduate Introduction to Numerical Methods and Backward Error Analysis” has been selected by Computing Reviews as a notable book in computing in 2013. Computing Reviews Best of 2013 list consists of book and article nominations from reviewers, CR category editors, the editors-in-chief of journals, and others in the computing community.
Author: Philip R. Bevington
Publisher: McGraw-Hill Science, Engineering & Mathematics
ISBN:
Category : Mathematics
Languages : en
Pages : 362
Get Book Here
Book Description
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.
Author: Jack Merrin
Publisher: Createspace Independent Publishing Platform
ISBN: 9781975906658
Category :
Languages : en
Pages : 112
Get Book Here
Book Description
Great scientists master the math behind the science. Do you still delay mastering data analysis, keeping you from more accurate, rigorous, and higher certainty conclusions? Jack Merrin, Ph.D. Princeton University, is a physicist who has helped hundreds of students with math and physics, taught physics labs, and used error analysis through 25 years of research. You can surely learn the right statistical methods from Jack. Introduction to Error Analysis is more than a collection of ad-hoc statistical theory. It is an easy-to-read blueprint used by scientists for presenting correct results. Transform your experimental perspective to confidence. Learn reusable principles for each new scientific project. This book covers reporting measurements and uncertainties, propagation of error, combining results, curve fitting, essential statistical concepts, and much, much, more. You might love this book if: You are doing lab reports or actual research, and it's time to get serious about data analysis. You want to focus on the essential calculations, not on time-wasting theory. You want adaptable MATLAB code for each different calculation. Hey, no need to reinvent the wheel. You want to reach correct and unique results using the established convention. You want to know what is correct to spot bad scientific literature. Introduction to Error Analysis is the concise book you need to start building your successful scientific career. If you like easy-to-follow lessons, practical examples, insightful tips, and an author who actually cares about you getting it right, then you'll love Jack's book. Buy Introduction to Error Analysis to start refining your data analysis skills today!
Author: Herman J. C. Berendsen
Publisher: Cambridge University Press
ISBN: 1139497855
Category : Technology & Engineering
Languages : en
Pages : 239
Get Book Here
Book Description
All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
Author: J. E. Akin
Publisher: Elsevier
ISBN: 0080472753
Category : Technology & Engineering
Languages : en
Pages : 465
Get Book Here
Book Description
This key text is written for senior undergraduate and graduate engineering students. It delivers a complete introduction to finite element methods and to automatic adaptation (error estimation) that will enable students to understand and use FEA as a true engineering tool. It has been specifically developed to be accessible to non-mathematics students and provides the only complete text for FEA with error estimators for non-mathematicians. Error estimation is taught on nearly half of all FEM courses for engineers at senior undergraduate and postgraduate level; no other existing textbook for this market covers this topic. - The only introductory FEA text with error estimation for students of engineering, scientific computing and applied mathematics - Includes source code for creating and proving FEA error estimators
Author: Colin Cooke
Publisher: CRC Press
ISBN: 0203983629
Category : Science
Languages : en
Pages : 128
Get Book Here
Book Description
Understanding, designing and conducting experiments is at the heart of science. This text introduces the fundamental principles on which physicists should build a thorough experimental approach to their discipline.
Author: Carl James
Publisher: Routledge
ISBN: 1317890299
Category : Language Arts & Disciplines
Languages : en
Pages : 282
Get Book Here
Book Description
Errors in Language Learning and Use is an up-to-date introduction and guide to the study of errors in language, and is also a critical survey of previous work. Error Analysis occupies a central position within Applied Linguistics, and seeks to clarify questions such as `Does correctness matter?', `Is it more important to speak fluently and write imaginatively or to communicate one's message?' Carl James provides a scholarly and well-illustrated theoretical and historical background to the field of Error Analysis. The reader is led from definitions of error and related concepts, to categorization of types of linguistic deviance, discussion of error gravities, the utility of teacher correction and towards writing learner profiles. Throughout, the text is guided by considerable practical experience in language education in a range of classroom contexts worldwide.
Author: Luis Tenorio
Publisher: SIAM
ISBN: 1611974917
Category : Mathematics
Languages : en
Pages : 275
Get Book Here
Book Description
Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.
