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Essentials of statistical inference /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Essentials of statistical inference // G.A. Young, R.L. Smith.
作者:	Young, G. A.
其他作者:	Smith, Richard L.,
面頁冊數:	1 online resource (x, 225 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Probabilities. -
電子資源:	https://doi.org/10.1017/CBO9780511755392
ISBN:	9780511755392 (ebook)

Essentials of statistical inference /
Young, G. A.

Essentials of statistical inference /G.A. Young, R.L. Smith. - 1 online resource (x, 225 pages) :digital, PDF file(s). - Cambridge series on statistical and probabilistic mathematics ;16. - Cambridge series on statistical and probabilistic mathematics ;32..

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Decision theory -- Beyesian methods -- Hypothesis testing -- Special models -- Sufficiency and completeness -- Two-sided tests and conditional inference -- Likelihood theory -- Higher-order theory -- Predictive inference -- Bootstrap methods.

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.

ISBN: 9780511755392 (ebook)Subjects--Topical Terms:

527847
Probabilities.

LC Class. No.: QA276 / .Y66 2005

Dewey Class. No.: 519.5

Essentials of statistical inference /
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520 $a 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.
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