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The Resource Introduction to applied Bayesian statistics and estimation for social scientists, Scott M. Lynch, (electronic resource)

Introduction to applied Bayesian statistics and estimation for social scientists, Scott M. Lynch, (electronic resource)

Label
Introduction to applied Bayesian statistics and estimation for social scientists
Title
Introduction to applied Bayesian statistics and estimation for social scientists
Statement of responsibility
Scott M. Lynch
Creator
Subject
Language
eng
Summary
Lynch covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of the book is that it covers models that are most commonly used on social science research
Member of
http://library.link/vocab/creatorDate
1971-
http://library.link/vocab/creatorName
Lynch, Scott M.
Dewey number
  • 300.1/519542
  • 300.727
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Statistics for social science and public policy
http://library.link/vocab/subjectName
  • Social sciences
  • Bayesian statistical decision theory
  • Social Science
Label
Introduction to applied Bayesian statistics and estimation for social scientists, Scott M. Lynch, (electronic resource)
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. [345]-351) and index
Color
multicolored
Contents
  • Modern model estimation part 1 : Gibbs sampling
  • 5.
  • Modern model estimation part 2 : Metropolis-Hastings sampling
  • 6.
  • Evaluating Markov chain Monte Carlo algorithms and model fit
  • 7.
  • linear regression model
  • 8.
  • Generalized linear models
  • 9.
  • Machine generated contents note:
  • Introduction to hierarchical models
  • 10.
  • Introduction to multivariate regression models
  • 11.
  • Conclusion
  • A.
  • Background mathematics
  • 1.
  • Introduction
  • 2.
  • Probability theory and classical statistics
  • 3.
  • Basics of Bayesian statistics
  • 4.
Control code
ocn655869069
Dimensions
unknown
Extent
1 online resource (xxviii, 357 p.)
Form of item
online
Isbn
9780387709598
Isbn Type
(electronic bk.)
Other physical details
ill
Specific material designation
remote
System control number
(OCoLC)655869069
Label
Introduction to applied Bayesian statistics and estimation for social scientists, Scott M. Lynch, (electronic resource)
Publication
Bibliography note
Includes bibliographical references (p. [345]-351) and index
Color
multicolored
Contents
  • Modern model estimation part 1 : Gibbs sampling
  • 5.
  • Modern model estimation part 2 : Metropolis-Hastings sampling
  • 6.
  • Evaluating Markov chain Monte Carlo algorithms and model fit
  • 7.
  • linear regression model
  • 8.
  • Generalized linear models
  • 9.
  • Machine generated contents note:
  • Introduction to hierarchical models
  • 10.
  • Introduction to multivariate regression models
  • 11.
  • Conclusion
  • A.
  • Background mathematics
  • 1.
  • Introduction
  • 2.
  • Probability theory and classical statistics
  • 3.
  • Basics of Bayesian statistics
  • 4.
Control code
ocn655869069
Dimensions
unknown
Extent
1 online resource (xxviii, 357 p.)
Form of item
online
Isbn
9780387709598
Isbn Type
(electronic bk.)
Other physical details
ill
Specific material designation
remote
System control number
(OCoLC)655869069

Library Locations

    • InternetBorrow it
      Albany, Auckland, 0632, NZ
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