M-statistics : optimal statistical inference for a small sample / Eugene Demidenko

By: Demidenko, Eugene [author]
Language: English Publisher: Hoboken, NJ : John Wiley & Sons, Inc., ©2023Description: x, 222 pages : illustrations ; 26 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781119891796Subject(s): Mathematical statisticsDDC classification: 519.54 Summary: "M-statistics: A New Statistical Perspective introduces a new approach for statistical interference, redesigning the fundamentals of statistics and improving on the classical methods we already use. The author discusses the development of new criteria for efficient estimation and delves into how two methods for statistical intereference are combined under one umbrella to create 'M statistics.' This book develops novel confidence intervals and statistical tests for statistical parameters including effect size, binomial probability, and Poisson rate, ensuring unbiased tests are developed alongside this. Suitable for professionals and students alike, this theoretical book explains how new approaches work for statistical applications and is accompanied with a GitHub repository hosting the R code for every new methodology presented."-- Provided by publisher
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BOOK BOOK HIGH SCHOOL LIBRARY - SHS
HIGH SCHOOL LIBRARY - SHS
SUBJECT REFERENCE 		519.54 D3952 2023 (Browse shelf) Available
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Includes index

Includes bibliographical references : p. 215 - 217

"M-statistics: A New Statistical Perspective introduces a new approach for statistical interference, redesigning the fundamentals of statistics and improving on the classical methods we already use. The author discusses the development of new criteria for efficient estimation and delves into how two methods for statistical intereference are combined under one umbrella to create 'M statistics.' This book develops novel confidence intervals and statistical tests for statistical parameters including effect size, binomial probability, and Poisson rate, ensuring unbiased tests are developed alongside this. Suitable for professionals and students alike, this theoretical book explains how new approaches work for statistical applications and is accompanied with a GitHub repository hosting the R code for every new methodology presented."-- Provided by publisher

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