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Sampling Statistics


Sampling Statistics


Wiley Series in Survey Methodology, Band 560 1. Aufl.

von: Wayne A. Fuller

123,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 20.09.2011
ISBN/EAN: 9781118211113
Sprache: englisch
Anzahl Seiten: 472

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Beschreibungen

<b>Discover the latest developments and current practices in survey sampling</b> <p>Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essential to planning statistical research and the design of experiments. <i>Sampling Statistics</i> presents estimation techniques and sampling concepts to facilitate the application of model-based procedures to survey samples.</p> <p>The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population. The development of the theory of complex sampling methods is detailed, and subsequent chapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponse adjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data are used for the estimation of parameters for a subject matter model.</p> <p>The author draws upon his extensive experience with survey samples in the book's numerous examples. Both the production of "general use" databases and the analytic study of a limited number of characteristics are discussed. Exercises at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques, and the references provide further resources for study.</p> <p><i>Sampling Statistics</i> is an ideal book for courses in survey sampling at the graduate level. It is also a valuable reference for practicing statisticians who analyze survey data or are involved in the design of sample surveys.</p>
<p>Preface ix</p> <p>List of Tables xi</p> <p>List of Principal Results xiii</p> <p>List of Examples xv</p> <p>1 Probability Sampling from a Finite Universe 1</p> <p>2 Use of Auxiliary Information in Estimation 95</p> <p>3 Use of Auxiliary Information in Design 181</p> <p>4 Replication Variance Estimation 251</p> <p>5 Models Used in Conjunction with Sampling 281</p> <p>6 Analytic Studies 341</p> <p>References 391</p> <p>Index 449</p>
<p><b>WAYNE A. FULLER, P<small>H</small>D,</b> is Distinguished Professor Emeritus in the Departments of Statistics and Economics at Iowa State University. He has previously served as principal investigator on research agreements with the U.S. Census Bureau, the Natural Resources Conservation Service, the National Agricultural Statistics Service, and the Bureau of Labor Statistics. Dr. Fuller is also a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Biometric Society, and is an elected member of the International Statistical Institute. He is the author of <i>Introduction to Statistical Time Series</i> and <i>Measurement Error Models,</i> both published by Wiley.
<p><b>Discover the latest developments and current practices in survey sampling</b> <p>Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essential to planning statistical research and the design of experiments. <i>Sampling Statistics</i> presents estimation techniques and sampling concepts to facilitate the application of model-based procedures to survey samples. <p>The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population. The development of the theory of complex sampling methods is detailed, and subsequent chapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponse adjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data are used for the estimation of parameters for a subject matter model. <p>The author draws upon his extensive experience with survey samples in the book's numerous examples. Both the production of "general use" databases and the analytic study of a limited number of characteristics are discussed. Exercises at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques, and the references provide further resources for study. <p><i>Sampling Statistics</i> is an ideal book for courses in survey sampling at the graduate level. It is also a valuable reference for practicing statisticians who analyze survey data or are involved in the design of sample surveys.

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