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Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask

  • Peter Young

Part of the SpringerBriefs in Physics book series (SpringerBriefs in Physics)

Table of contents

  1. Front Matter
    Pages i-x
  2. Peter Young
    Pages 1-1
  3. Peter Young
    Pages 3-19
  4. Peter Young
    Pages 21-53
  5. Back Matter
    Pages 55-85

About this book

Introduction

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 how to proceed for combinations of measured values. Techniques for fitting data to a given set of models will be described in the second part of these notes. This primer equips readers to properly derive the results covered, presenting the content in a style suitable for a physics audience. It also includes scripts in python, perl and gnuplot for performing a number of tasks in data analysis and fitting, thereby providing readers with a useful reference guide.

Keywords

Analysis and Fitting of Experimental Data Data Analysis Textbook Distributions of Fitted Parameters Fitting of Correlated Data Maximum Likelihood versus Bayesian Approaches Perl and Gnuplot Scripts for Data Fitting Python Scripts for Data Analysis and Fitting Scripts for Data Analysis and Fitting Tasks

Authors and affiliations

  • Peter Young
    • 1
  1. 1.Physics DepartmentUniversity of CaliforniaSanta CruzUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-19051-8
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Cham
  • eBook Packages Physics and Astronomy
  • Print ISBN 978-3-319-19050-1
  • Online ISBN 978-3-319-19051-8
  • Series Print ISSN 2191-5423
  • Series Online ISSN 2191-5431
  • Buy this book on publisher's site