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    Data Analysis

Data Analysis

Devinderjit Sivia, John Skilling
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      Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimentaldesign.The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.
      Format: CONTRIBUTORS: Devinderjit Sivia, John Skilling EAN: 9780198568322 COUNTRY: United Kingdom PAGES: WEIGHT: 408 g HEIGHT: 233 cm
      PUBLISHED BY: Oxford University Press DATE PUBLISHED: 2006-06-01 CITY: GENRE: MATHEMATICS / Probability & Statistics / Bayesian Analysis WIDTH: 159 cm SPINE:

      Book Themes:

      Probability and statistics, Statistical physics

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      Devinderjit Singh SiviaRutherford Appleton LaboratoryChiltonOxonOX11 5DJJohn SkillingMaximum Entropy Data Consultants42 Southgate StreetBury St EdmondsSuffolkIP33 2AZ
      Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimentaldesign.The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.
      Format: CONTRIBUTORS: Devinderjit Sivia, John Skilling EAN: 9780198568322 COUNTRY: United Kingdom PAGES: WEIGHT: 408 g HEIGHT: 233 cm
      PUBLISHED BY: Oxford University Press DATE PUBLISHED: 2006-06-01 CITY: GENRE: MATHEMATICS / Probability & Statistics / Bayesian Analysis WIDTH: 159 cm SPINE:

      Book Themes:

      Probability and statistics, Statistical physics

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      Be the first to write a review
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      Devinderjit Singh SiviaRutherford Appleton LaboratoryChiltonOxonOX11 5DJJohn SkillingMaximum Entropy Data Consultants42 Southgate StreetBury St EdmondsSuffolkIP33 2AZ

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