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Home > Art, Film & Photography > Statistical Principles: Pareto Principle, Likelihood Principle, Sufficient Statistic, Hardy-Weinberg Principle, Principle of Maximum Entropy
Statistical Principles: Pareto Principle, Likelihood Principle, Sufficient Statistic, Hardy-Weinberg Principle, Principle of Maximum Entropy

Statistical Principles: Pareto Principle, Likelihood Principle, Sufficient Statistic, Hardy-Weinberg Principle, Principle of Maximum Entropy


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About the Book

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Pareto Principle, Likelihood Principle, Sufficient Statistic, Hardy-weinberg Principle, Principle of Maximum Entropy, Principle of Indifference, Orthogonality Principle, Craps Principle, Conditionality Principle, Coherence, Cromwell's Rule, Magnitude and Frequency Principle, Sparsity-Of-Effects Principle. Excerpt: In probability theory and statistics, coherence can have two meanings. References (URLs online) A hyperlinked version of this chapter is at The conditionality principle is a Fisherian principle of statistical inference that Allan Birnbaum formally defined and studied in his 1962 JASA article. Together with the sufficiency principle, Birnbaum's version of the principle implies the famous likelihood principle . Although the relevance of the proof to data analysis remains controversial among statisticians, many Bayesians and likelihoodists consider the likelihood principle foundational for statistical inference. Formulation The conditionality principle makes an assertion about an experiment E that can be described as a mixture of several component experiments Eh where h is an ancillary statistic (i.e. a statistic whose probability distribution does not depend on unknown parameter values). This means that observing a specific outcome x of experiment E is equivalent to observing the value of h and taking an observation xh from the component experiment Eh . The conditionality principle can be formally stated thus: Conditionality Principle: If E is any experiment having the form of a mixture of component experiments Eh, then for each outcome ( E h, x h ) of E, the evidential meaning of any outcome x of any mixture experiment E is the same as that of the corresponding outcome xh of the corresponding component experiment Eh, ignoring the over-all structure of the mixed ...


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Product Details
  • ISBN-13: 9781155282695
  • Publisher: Books LLC
  • Publisher Imprint: Books LLC
  • Height: 152 mm
  • Sub Title: Pareto Principle, Likelihood Principle, Sufficient Statistic, Hardy-Weinberg Principle, Principle of Maximum Entropy
  • Width: 229 mm
  • ISBN-10: 1155282698
  • Publisher Date: 02 May 2010
  • Binding: Paperback
  • Spine Width: 5 mm
  • Weight: 122 gr


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