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Author: S. Sampath Publisher: CRC Press ISBN: 9780849309809 Category : Mathematics Languages : en Pages : 208
Book Description
"The book presents in detail several sampling schemes like simple random sampling, unequal probability sampling methods, systematic, stratified, cluster and multistage sampling. In addition to sampling schemes several estimating methods which include ratio and regression estimators are also discussed. The use of superpopulation models is also covered in detail. Some recent developments which include estimation of distribution functions, adaptive sampling schemes etc. are also presented."--BOOK JACKET.
Author: S. Sampath Publisher: Alpha Science Int'l Ltd. ISBN: 9781842652145 Category : Sampling (Statistics) Languages : en Pages : 218
Book Description
Sampling Theory and Methods presents in detail several sampling schemes like simple random sampling, unequal probability sampling methods, systematic, stratified, cluster and multistage sampling. In addition to sampling schemes a number of estimating methods which include ratio and regression estimators are also discussed. The use of superpopulation models is covered in detail along with recent developments including estimation of distribution functions, adaptive sampling schemes etc. New to the Second Edition: *Contents reorganized to establish a coherent link between various concepts *Several numerical examples associated with real life solutions for bringing out the relevance of theory in real life context
Author: Changbao Wu Publisher: Springer Nature ISBN: 3030442462 Category : Social Science Languages : en Pages : 371
Book Description
The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice. These related aspects of survey methodology rarely appear together under a single connected roof, making this book a unique combination of materials for teaching, research and practice in survey sampling. Basic knowledge of probability theory and statistical inference is assumed, but no prior exposure to survey sampling is required. The first part focuses on the design-based approach to finite population sampling. It contains a rigorous coverage of basic sampling designs, related estimation theory, model-based prediction approach, and model-assisted estimation methods. The second part stems from original research conducted by the authors as well as important methodological advances in the field during the past three decades. Topics include calibration weighting methods, regression analysis and survey weighted estimating equation (EE) theory, longitudinal surveys and generalized estimating equations (GEE) analysis, variance estimation and resampling techniques, empirical likelihood methods for complex surveys, handling missing data and non-response, and Bayesian inference for survey data. The third part provides guidance and tools on practical aspects of large-scale surveys, such as training and quality control, frame construction, choices of survey designs, strategies for reducing non-response, and weight calculation. These procedures are illustrated through real-world surveys. Several specialized topics are also discussed in detail, including household surveys, telephone and web surveys, natural resource inventory surveys, adaptive and network surveys, dual-frame and multiple frame surveys, and analysis of non-probability survey samples. This book is a self-contained introduction to survey sampling that provides a strong theoretical base with coverage of current research trends and pragmatic guidance and tools for conducting surveys.
Author: Raghunath Arnab Publisher: Academic Press ISBN: 0128118970 Category : Mathematics Languages : en Pages : 932
Book Description
Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling. The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students. Covers a wide spectrum of topics on survey sampling and statistics Serves as an ideal text for graduate students and researchers in survey sampling theory and applications Contains material on recent developments in survey sampling not covered in other books Illustrates theories using numerical examples and exercises
Author: Arijit Chaudhuri Publisher: CRC Press ISBN: 149877475X Category : Mathematics Languages : en Pages : 241
Book Description
This venture aspires to be a mix of a textbook at the undergraduate and postgraduate levels and a monograph to catch the attention of researchers in theoretical and practical aspects of survey sampling at diverse levels demanding a comprehensive review of what useful materials have preceded, with an eye to what beacons to the depth of the imminent future.
Author: Arijit Chaudhuri Publisher: CRC Press ISBN: 1420028634 Category : Mathematics Languages : en Pages : 416
Book Description
Since publication of the first edition in 1992, the field of survey sampling has grown considerably. This new edition of Survey Sampling: Theory and Methods has been updated to include the latest research and the newest methods. The authors have undertaken the daunting task of surveying the sampling literature of the past decade to provide an outst
Book Description
This is a comprehensive exposition of survey sampling useful both to the students of statistics for the course on sample survey and to the survey statisticians and practitioners involved in consultancy services, marketing, opinion polls, and so on. The text offers updated review of difficult classical techniques of survey sampling, besides covering prediction-theoretic approach of survey sampling and nonsampling errors. NEW TO THIS EDITION Two new chapters—Nonparametric Methods of Variance Estimation (Chapter 19) and Analysis of Complex Surveys (Chapter 20)—have been added. These would greatly benefit the readers. KEY FEATURES Covers concepts of unequal probability sampling. Provides problems of making inference from finite population using tools of classical inference. Describes nonsampling errors including Randomised Response Techniques. Gives over 70 worked-out examples and more than 120 problems and solutions. Supplies live data from India and Sweden—in examples and exercises. What the Reviewer says: This is a very comprehensive modern text on survey sampling with a strong slant towards theoretical results. The book is an excellent reference book and would be a good graduate level sampling text for a course with an emphasis on sampling theory. — JESSE C. ARNOLD, Virginia Polytechnic Institute and State University
Author: Pascal Ardilly Publisher: Springer Science & Business Media ISBN: 0387310754 Category : Social Science Languages : en Pages : 382
Book Description
Whenweagreedtoshareallofourpreparationofexercisesinsamplingtheory to create a book, we were not aware of the scope of the work. It was indeed necessary to compose the information, type out the compilations, standardise the notations and correct the drafts. It is fortunate that we have not yet measured the importance of this project, for this work probably would never have been attempted! In making available this collection of exercises, we hope to promote the teaching of sampling theory for which we wanted to emphasise its diversity. The exercises are at times purely theoretical while others are originally from real problems, enabling us to approach the sensitive matter of passing from theory to practice that so enriches survey statistics. The exercises that we present were used as educational material at the École Nationale de la Statistique et de l’Analyse de l’Information (ENSAI), where we had successively taught sampling theory. We are not the authors of all the exercises. In fact, some of them are due to Jean-Claude Deville and Laurent Wilms. We thank them for allowing us to reproduce their exercises. It is also possible that certain exercises had been initially conceived by an author that we have not identi?ed. Beyondthe contribution of our colleagues, and in all cases, we do not consider ourselves to be the lone authors of these exercises:they actually form part of a common heritagefrom ENSAI that has been enriched and improved due to questions from students and the work of all the demonstrators of the sampling course at ENSAI.
Author: John J. Benedetto Publisher: Springer Science & Business Media ISBN: 1461201438 Category : Mathematics Languages : en Pages : 423
Book Description
A state-of-the-art edited survey covering all aspects of sampling theory. Theory, methods and applications are discussed in authoritative expositions ranging from multi-dimensional signal analysis to wavelet transforms. The book is an essential up-to-date resource.
Author: Luca Martino Publisher: Springer ISBN: 331972634X Category : Computers Languages : en Pages : 289
Book Description
This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, designed to efficiently address common real-world practical problems, are introduced and discussed in detail. In turn, the monograph presents fundamental results and methodologies in the field, elaborating and developing them into the latest techniques. The theory and methods are illustrated with a varied collection of examples, which are discussed in detail in the text and supplemented with ready-to-run computer code. The main problem addressed in the book is how to generate independent random samples from an arbitrary probability distribution with the weakest possible constraints or assumptions in a form suitable for practical implementation. The authors review the fundamental results and methods in the field, address the latest methods, and emphasize the links and interplay between ostensibly diverse techniques.
Author: S. Sampath
Author: S. Sampath
Author: Changbao Wu
Author: Raghunath Arnab
Author: Arijit Chaudhuri
Author: Mankal Narasinha Murthy
Author: Arijit Chaudhuri
Author: PARIMAL MUKHOPADHYAY
Author: Pascal Ardilly
Author: John J. Benedetto
Author: Luca Martino