A Sound Basis for the Theory of Statistical Inference
Measuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct.
The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.
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Michael Evans began his career in journalism working for a local East London newspaper before making it to Fleet Street in 1970. He worked for the Daily Express for sixteen years, first as a general reporter, then as the home affairs correspondent and, finally, as the defence and diplomatic correspondent. Michael was headhunted by The Times in 1986 where he was appointed Whitehall correspondent before being promoted to defence correspondent, then defence editor - a post he held for twelve years. He was The Times' Pentagon correspondent in Washington from 2010 to 2013, and today he continues to write on defence and intelligence issues for the newspaper. The author of six books, Michael is married, has three sons and lives in London.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A Sound Basis for the Theory of Statistical InferenceMeasuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct.The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application. 252 pp. Englisch. Bestandsnummer des Verkäufers 9781032098562
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