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An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements

An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements

An Introduction to Error Analysis: The Study of Uncertainties in Physical
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An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements Hardback - 2015

by John R. Taylor; Kathleen L. Purvis-Roberts; William M. Stigliani

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3rd edition NO-PA16APR2015-KAP. Hardback. New.
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Details

  • Title An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements
  • Author John R. Taylor; Kathleen L. Purvis-Roberts; William M. Stigliani
  • Binding Hardback
  • Condition New
  • Pages 392
  • Volumes 1
  • Language ENG
  • Publisher University Science Books
  • Publication date 3rd edition NO-PA16APR2015-K
  • Features Bibliography, Index
  • Bookseller's Inventory # 6396279676
  • ISBN 9781940380148 / 1940380146
  • Weight 1.77 lbs (0.80 kg)
  • Dimensions 10.18 x 7.3 x 0.81 in (25.86 x 18.54 x 2.06 cm)
  • Category Science
  • Library of Congress subjects Mathematical physics, Physical measurements
  • Library of Congress Catalogue Number 2022003415
  • Dewey Decimal Code 530.801
  • Quantity available 3

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Reader reviews for An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements

From the publisher

John R. Taylor (TM)s best-selling text will be released in a new third edition that features Bayesian statistics and updated new chapter-ending problems throughout. Previously translated into nine languages, this brilliant little text introduces the study of uncertainties to lower division science students using familiar examples.
This remarkable text by John R. Taylor has been a non-stop best-selling international hit since it was first published forty years ago. However, the two-plus decades since the second edition was released have seen two dramatic developments; the huge rise in popularity of Bayesian statistics, and the continued increase in the power and availability of computers and calculators. In response to the former, Taylor has added a full chapter dedicated to Bayesian thinking, introducing conditional probabilities and Bayes (TM) theorem. The several examples presented in the new third edition are intentionally very simple, designed to give readers a clear understanding of what Bayesian statistics is all about as their first step on a journey to become practicing Bayesians. In response to the second development, Taylor has added a number of chapter-ending problems that will encourage readers to learn how to solve problems using computers. While many of these can be solved using programs such as Matlab or Mathematica, almost all of them are stated to apply to commonly available spreadsheet programs like Microsoft Excel. These programs provide a convenient way to record and process data and to calculate quantities like standard deviations, correlation coefficients, and normal distributions; they also have the wonderful ability " if students construct their own spreadsheets and avoid the temptation to use built-in functions " to teach the meaning of these concepts.
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