Essentials of Statistical Inference (Cambridge Series in Statistical and Probabilistic Mathematics)

by G. A. Young and R. L. Smith

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Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between them. Computational ideas are explained, as well as basic mathematical theory. Written in a lucid and informal style, this concise text provides both basic material on the main approaches to inference, as well as more advanced material on developments in statistical theory, including: material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems.
  • ISBN13 9780521548663
  • Publish Date 29 March 2010 (first published 25 July 2005)
  • Publish Status Active
  • Out of Print 6 June 2022
  • Publish Country GB
  • Imprint Cambridge University Press
  • Format Paperback (US Trade)
  • Pages 236
  • Language English