Ratio Estimators in Simple Random Sampling Using Information on Auxiliary Attribute PDF Download
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Author: Rajesh Singh
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
Some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute, are proposed.
Author: Rajesh Singh
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
Some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute, are proposed.
Author: Rajesh Singh
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
Some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute, are proposed.
Author: Hulya Cingi
Publisher: Bentham Science Publishers
ISBN: 1608050122
Category : Mathematics
Languages : en
Pages : 129
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Book Description
"Ratio Method of Estimation - This is an ideal textbook for researchers interested in sampling methods, survey methodologists in government organizations, academicians, and graduate students in statistics, mathematics and biostatistics. This textbook makes"
Author: Sarjinder Singh
Publisher: Springer Science & Business Media
ISBN: 9781402017070
Category : Mathematics
Languages : en
Pages : 640
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Book Description
A comprehensive expose of basic and advanced sampling techniques along with their applications in the diverse fields of science and technology.
Author: Munir Ahmad
Publisher: Cambridge Scholars Publishing
ISBN: 1443825220
Category : Social Science
Languages : en
Pages : 240
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Book Description
Ranked Set Sampling is one of the new areas of study in this region of the world and is a growing subject of research. Recently, researchers have paid attention to the development of the types of sampling; though it was not welcome in the beginning, it has numerous advantages over the classical sampling techniques. Ranked Set Sampling is doubly random and can be used in any survey designs. The Pakistan Journal of Statistics had attracted statisticians and samplers around the world to write up aspects of Ranked Set Sampling. All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics. The subject is still a hot topic for MPhil and PhD students for their dissertations.
Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292622234
Category : Business & Economics
Languages : en
Pages : 152
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Book Description
This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Author: Pandurang Vasudeo Sukhatme
Publisher:
ISBN:
Category : Sampling (Statistics).
Languages : en
Pages : 528
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Book Description
Basic theory: simple random sampling. Sampling with varying probabilities. Stratified sampling. Ratio method of estimation. Regression method estimation. Choice of sampling unit. Sub-sampling. Systematic sampling. Non-sampling errors.
Author: Rajesh Singh, Florentin Smarandache
Publisher: Infinite Study
ISBN: 159973348X
Category : Mathematics
Languages : en
Pages : 56
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Book Description
The present book aims to present some improved estimators using auxiliary and attribute information in case of simple random sampling and stratified random sampling and in some cases when non-response is present. This volume is a collection of five papers, written by seven co-authors (listed in the order of the papers): Sachin Malik, Rajesh Singh, Florentin Smarandache, B. B. Khare, P. S. Jha, Usha Srivastava and Habib Ur. Rehman.
Author: Kirk Wolter
Publisher: Springer Science & Business Media
ISBN: 9780387406220
Category : Education
Languages : en
Pages : 504
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Book Description
Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.
Author: Thomas Lumley
Publisher: John Wiley & Sons
ISBN: 111821093X
Category : Mathematics
Languages : en
Pages : 329
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Book Description
A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.
