ShopSpell

Bayesian Statistical Inference [Paperback]

$58.99       (Free Shipping)
78 available
  • Category: Books (Mathematics)
  • Author:  Iversen, Gudmund R.
  • Author:  Iversen, Gudmund R.
  • ISBN-10:  0803923287
  • ISBN-10:  0803923287
  • ISBN-13:  9780803923287
  • ISBN-13:  9780803923287
  • Publisher:  SAGE Publications, Inc
  • Publisher:  SAGE Publications, Inc
  • Pages:  80
  • Pages:  80
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Jun-1984
  • Pub Date:  01-Jun-1984
  • SKU:  0803923287-11-MPOD
  • SKU:  0803923287-11-MPOD
  • Item ID: 103234451
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 01 to Oct 03
  • Notes: Brand new books. Buy now.
Empirical researchers, for whom Iversen's volume provides an introduction, have generally lacked a grounding in the methodology of Bayesian inference. As a result, applications are few. After outlining the limitations of classical statistical inference, the author proceeds through a simple example to explain Bayes' theorem and how it may overcome these limitations. Typical Bayesian applications are shown, together with the strengths and weaknesses of the Bayesian approach. This monograph thus serves as a companion volume for Henkel's Tests of Significance (QASS vol 4).Empirical researchers, for whom Iversen's volume provides an introduction, have generally lacked a grounding in the methodology of Bayesian inference. As a result, applications are few. After outlining the limitations of classical statistical inference, the author proceeds through a simple example to explain Bayes' theorem and how it may overcome these limitations. Typical Bayesian applications are shown, together with the strengths and weaknesses of the Bayesian approach. This monograph thus serves as a companion volume for Henkel's Tests of Significance (QASS vol 4).Thomas Bayes and Statistical Inference
Classical Statistical Inference
Bayes' Theorem
Bayesian Methods for a Proportion
Bayesian Methods for Other Parameters
Prior Distributions
Bayesian Difficulties
Bayesian Strengths
Add Review