Essentials of Statistical Inference
Essentials of Statistical Inference by G. A. Young is an illustrated textbook published by Cambridge University Press on March 29, 2010. This edition spans 236 pages and is written in English, providing a comprehensive overview of statistical inference concepts and results, focusing on the Bayesian, frequentist, and Fisherian approaches.
Readers will find a detailed exploration of both basic mathematical theory and advanced topics, including Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods, and conditional inference. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, this book serves as a resource for understanding the contrasts between different statistical methodologies.
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This textbook presents the concepts and results underlying the Bayesian, frequentist, and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers basic mathematical theory as well as more advanced material, including such contemporary topics as Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods, and conditional inference.
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