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Selected topics in statistical infer...

Pal, Manisha.

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Selected topics in statistical inference = theory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Selected topics in statistical inference/ by Manisha Pal, Bikas K. Sinha.
Reminder of title:	theory and applications /
Author:	Pal, Manisha.
other author:	Sinha, Bikas K.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xvii, 142 p. :ill., digital ;24 cm.
[NT 15003449]:	Glimpses of the Book -- Sequential Binomial Estimation -- Use of Additional Resources in Finite Population Inference -- Notion of sufficiency in statistical inference - Theory and Applications -- Estimation of the Unknown Size of a Finite Population with Special Features -- Unbiased Estimation of Reliability in Exponential Samples.
Contained By:	Springer Nature eBook
Subject:	Mathematical statistics. -
Online resource:	https://doi.org/10.1007/978-981-97-2592-2
ISBN:	9789819725922

Selected topics in statistical inference = theory and applications /
Pal, Manisha.

Selected topics in statistical inferencetheory and applications /[electronic resource] :by Manisha Pal, Bikas K. Sinha. - Singapore :Springer Nature Singapore :2024. - xvii, 142 p. :ill., digital ;24 cm.

Glimpses of the Book -- Sequential Binomial Estimation -- Use of Additional Resources in Finite Population Inference -- Notion of sufficiency in statistical inference - Theory and Applications -- Estimation of the Unknown Size of a Finite Population with Special Features -- Unbiased Estimation of Reliability in Exponential Samples.

This book focuses exclusively on the domain of parametric inference and that, too, from a reader's perspective, i.e., covering only point estimation of parameter(s) It covers those topics in parametric inference which need clarity of exposure to students, researchers, and teachers alike; mere statements of theorems and proofs may not always reveal the inner beauty and significance of some aspects of inference. To ensure clarity, the book discusses the following topics at an advanced level-(1) sequential (unbiased) point estimation of 'p' and its functions; generalization to trinomial and tetranomial populations; (2) some aspects of the use of additional resources in finite population inference; (3) the concept of sufficiency vis-à-vis the notion of sufficient experiments and comparison of experiments; (4) estimation of the size of a finite population with special features; and (5) unbiased estimation of reliability in exponential samples and other settings. This book provides a platform for thought-provoking, creative, and challenging discussions on a variety of topics in statistical estimation theory, it is also ideal for research methodology course for statistics research scholars, and for clarification of basic ideas in topics discussed at basic/advanced levels.

ISBN: 9789819725922

Standard No.: 10.1007/978-981-97-2592-2doiSubjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.54

Selected topics in statistical inference = theory and applications /
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520 $a This book focuses exclusively on the domain of parametric inference and that, too, from a reader's perspective, i.e., covering only point estimation of parameter(s) It covers those topics in parametric inference which need clarity of exposure to students, researchers, and teachers alike; mere statements of theorems and proofs may not always reveal the inner beauty and significance of some aspects of inference. To ensure clarity, the book discusses the following topics at an advanced level-(1) sequential (unbiased) point estimation of 'p' and its functions; generalization to trinomial and tetranomial populations; (2) some aspects of the use of additional resources in finite population inference; (3) the concept of sufficiency vis-à-vis the notion of sufficient experiments and comparison of experiments; (4) estimation of the size of a finite population with special features; and (5) unbiased estimation of reliability in exponential samples and other settings. This book provides a platform for thought-provoking, creative, and challenging discussions on a variety of topics in statistical estimation theory, it is also ideal for research methodology course for statistics research scholars, and for clarification of basic ideas in topics discussed at basic/advanced levels.
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