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Autor(en): 
  • John R. Taylor
  • An Introduction to Error Analysis, third edition: The Study of Uncertainties in Physical Measurements 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

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    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  August 2022  
    Genre:  Naturwissensch., Medizin, Technik 
     
    alchemy / American History / Biology / Buddhism / Business / chemistry / chemistry book / chemistry gifts
    ISBN:  9781940380087 
    EAN-Code: 
    9781940380087 
    Verlag:  MIT Press 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 255 mm / B 174 mm / D 24 mm 
    Gewicht:  702 gr 
    Seiten:  392 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    John R. Taylor'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' 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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