Borrow it
 Architecture Library
 Bizzell Memorial Library
 Boorstin Collection
 Chinese Literature Translation Archive
 Engineering Library
 Fine Arts Library
 Harry W. Bass Business History Collection
 History of Science Collections
 John and Mary Nichols Rare Books and Special Collections
 Library Service Center
 Price College Digital Library
 Western History Collections
The Resource Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver
Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver
Resource Information
The item Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.This item is available to borrow from all library branches.
Resource Information
The item Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.
This item is available to borrow from all library branches.
 Summary
 Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of realworld problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University
 Language
 eng
 Extent
 1 online resource (xi, 238 pages)
 Contents

 Recipes
 A Bit of Theory
 A Bit of Numerical Computation
 Single Parameter Models
 The Prior
 Multiparameters Models
 Nonrandom Data Collection
 Fitting Regression Models
 Model Checking and Sensitivity Analysis
 Bayesian vs Simple Methods
 Appendix: Probability Distributions
 Appendix: The third axiom of probability, conditional probability, independence and conditional independence
 Isbn
 9783319152875
 Label
 Bayesian methods for the physical sciences : learning from examples in astronomy and physics
 Title
 Bayesian methods for the physical sciences
 Title remainder
 learning from examples in astronomy and physics
 Statement of responsibility
 Stefano Andreon, Brian Weaver
 Subject

 Theoretical & mathematical astronomy
 Statistics
 Electronic books
 Bayesian statistical decision theory
 Mathematical physics
 MATHEMATICS  Probability & Statistics  General
 Mathematical physics
 Mathematical physics
 Astronomy, Astrophysics and Cosmology
 MATHEMATICS  Applied
 Probability & statistics
 Statistical astronomy
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Mathematical Methods in Physics
 Statistical astronomy
 Bayesian statistical decision theory
 Language
 eng
 Summary
 Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of realworld problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University
 Cataloging source
 N$T
 http://library.link/vocab/creatorName
 Andreon, Stefano
 Dewey number
 519.5/42
 Illustrations
 illustrations
 Index
 no index present
 LC call number
 QC20.7.B38
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 http://library.link/vocab/relatedWorkOrContributorName
 Weaver, Brian
 Series statement
 Springer series in astrostatistics,
 http://library.link/vocab/subjectName

 Bayesian statistical decision theory
 Mathematical physics
 Statistical astronomy
 MATHEMATICS
 MATHEMATICS
 Bayesian statistical decision theory
 Mathematical physics
 Statistical astronomy
 Statistics
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Astronomy, Astrophysics and Cosmology
 Mathematical Methods in Physics
 Mathematical physics
 Probability & statistics
 Theoretical & mathematical astronomy
 Label
 Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 Recipes  A Bit of Theory  A Bit of Numerical Computation  Single Parameter Models  The Prior  Multiparameters Models  Nonrandom Data Collection  Fitting Regression Models  Model Checking and Sensitivity Analysis  Bayesian vs Simple Methods  Appendix: Probability Distributions  Appendix: The third axiom of probability, conditional probability, independence and conditional independence
 Dimensions
 unknown
 Extent
 1 online resource (xi, 238 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9783319152875
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Note
 SpringerLink
 Other control number
 10.1007/9783319152875
 Other physical details
 illustrations (some color).
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number

 (OCoLC)909772452
 (OCoLC)ocn909772452
 Label
 Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 Recipes  A Bit of Theory  A Bit of Numerical Computation  Single Parameter Models  The Prior  Multiparameters Models  Nonrandom Data Collection  Fitting Regression Models  Model Checking and Sensitivity Analysis  Bayesian vs Simple Methods  Appendix: Probability Distributions  Appendix: The third axiom of probability, conditional probability, independence and conditional independence
 Dimensions
 unknown
 Extent
 1 online resource (xi, 238 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9783319152875
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Note
 SpringerLink
 Other control number
 10.1007/9783319152875
 Other physical details
 illustrations (some color).
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number

 (OCoLC)909772452
 (OCoLC)ocn909772452
Subject
 Astronomy, Astrophysics and Cosmology
 Bayesian statistical decision theory
 Bayesian statistical decision theory
 Electronic books
 MATHEMATICS  Applied
 MATHEMATICS  Probability & Statistics  General
 Mathematical Methods in Physics
 Mathematical physics
 Mathematical physics
 Mathematical physics
 Probability & statistics
 Statistical astronomy
 Statistical astronomy
 Statistics
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Theoretical & mathematical astronomy
Genre
Member of
Library Locations

Architecture LibraryBorrow itGould Hall 830 Van Vleet Oval Rm. 105, Norman, OK, 73019, US35.205706 97.445050



Chinese Literature Translation ArchiveBorrow it401 W. Brooks St., RM 414, Norman, OK, 73019, US35.207487 97.447906

Engineering LibraryBorrow itFelgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US35.205706 97.445050

Fine Arts LibraryBorrow itCatlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US35.210371 97.448244

Harry W. Bass Business History CollectionBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

History of Science CollectionsBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

John and Mary Nichols Rare Books and Special CollectionsBorrow it401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US35.207487 97.447906


Price College Digital LibraryBorrow itAdams Hall 102 307 West Brooks St., Norman, OK, 73019, US35.210371 97.448244

Western History CollectionsBorrow itMonnet Hall 630 Parrington Oval, Rm. 300, Norman, OK, 73019, US35.209584 97.445414
Embed (Experimental)
Settings
Select options that apply then copy and paste the RDF/HTML data fragment to include in your application
Embed this data in a secure (HTTPS) page:
Layout options:
Include data citation:
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.libraries.ou.edu/portal/Bayesianmethodsforthephysicalsciences/uB6JSk66cUE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.libraries.ou.edu/portal/Bayesianmethodsforthephysicalsciences/uB6JSk66cUE/">Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.libraries.ou.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.libraries.ou.edu/">University of Oklahoma Libraries</a></span></span></span></span></div>
Note: Adjust the width and height settings defined in the RDF/HTML code fragment to best match your requirements
Preview
Cite Data  Experimental
Data Citation of the Item Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver
Copy and paste the following RDF/HTML data fragment to cite this resource
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.libraries.ou.edu/portal/Bayesianmethodsforthephysicalsciences/uB6JSk66cUE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.libraries.ou.edu/portal/Bayesianmethodsforthephysicalsciences/uB6JSk66cUE/">Bayesian methods for the physical sciences : learning from examples in astronomy and physics, Stefano Andreon, Brian Weaver</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.libraries.ou.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.libraries.ou.edu/">University of Oklahoma Libraries</a></span></span></span></span></div>