Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
These notes describe how to average and fit numerical data that have been obtained either by simulation or measurement. Following an introduction on how to estimate various average values, they discuss how to determine error bars on those estimates, and h
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Peter Young
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
SpringerBriefs in Physics Editorial Board Egor Babaev, University of Massachusetts, Massachusetts, USA Malcolm Bremer, University of Bristol, Bristol, UK Xavier Calmet, University of Sussex, Sussex, UK Francesca Di Lodovico, Queen Mary University of London, London, UK Maarten Hoogerland, University of Auckland, Auckland, New Zealand Eric Le Ru, Victoria University of Wellington, Wellington, New Zealand Hans-Joachim Lewerenz, California Institute of Technology, Pasadena, USA James Overduin, Towson University, Towson, USA Vesselin Petkov, Concordia University, Concordia, Canada Charles H.-T. Wang, University of Aberdeen, Aberdeen, UK Andrew Whitaker, Queen’s University Belfast, Belfast, UK
More information about this series at http://www.springer.com/series/8902
Peter Young
Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask
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Peter Young Physics Department University of California Santa Cruz, CA USA
ISSN 2191-5423 SpringerBriefs in Physics ISBN 978-3-319-19050-1 DOI 10.1007/978-3-319-19051-8
ISSN 2191-5431
(electronic)
ISBN 978-3-319-19051-8
(eBook)
Library of Congress Control Number: 2015939824 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results rather than just quote them. The aim is put a lot of useful pedagogical material together in a convenient place.
Acknowledgments
I am grateful to Alexander Hartmann for inviting me to give a lecture at the Bad Honnef School on “Efficient Algorithms in Computatio
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