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Statistical Information: A Bayesian Perspective

1
Department of Statistics, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA
2
Instituto de Matemática e Estatística, Universidade de São Paulo, Rua do Matão 1010, 05508-900, São Paulo, Brazil
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Author to whom correspondence should be addressed.
Entropy 2012, 14(11), 2254-2264; https://doi.org/10.3390/e14112254
Received: 15 August 2012 / Revised: 28 September 2012 / Accepted: 1 November 2012 / Published: 7 November 2012
We explore the meaning of information about quantities of interest. Our approach is divided in two scenarios: the analysis of observations and the planning of an experiment. First, we review the Sufficiency, Conditionality and Likelihood principles and how they relate to trivial experiments. Next, we review Blackwell Sufficiency and show that sampling without replacement is Blackwell Sufficient for sampling with replacement. Finally, we unify the two scenarios presenting an extension of the relationship between Blackwell Equivalence and the Likelihood Principle. View Full-Text
Keywords: statistical information; Blackwell sufficiency; likelihood principle statistical information; Blackwell sufficiency; likelihood principle
MDPI and ACS Style

Stern, R.B.; Pereira, C.A.B. Statistical Information: A Bayesian Perspective. Entropy 2012, 14, 2254-2264.

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