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Author: Seymour Sudman
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 262
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Book Description
Discusses numerous sampling methods with emphasis on the less expensive techniques.
Author: Seymour Sudman
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 262
Get Book Here
Book Description
Discusses numerous sampling methods with emphasis on the less expensive techniques.
Author: Edward Blair
Publisher: SAGE Publications
ISBN: 1483346919
Category : Social Science
Languages : en
Pages : 191
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Book Description
Written for students and researchers who wish to understand the conceptual and practical aspects of sampling, this book is designed to be accessible without requiring advanced statistical training. It covers a wide range of topics, from the basics of sampling to special topics such as sampling rare populations, sampling organizational populations, and sampling visitors to a place. Using cases and examples to illustrate sampling principles and procedures, the book thoroughly covers the fundamentals of modern survey sampling, and addresses recent changes in the survey environment such as declining response rates, the rise of Internet surveys, the need to accommodate cell phones in telephone surveys, and emerging uses of social media and big data.
Author: Gary T. Henry
Publisher: SAGE Publications
ISBN: 1506320341
Category : Social Science
Languages : en
Pages : 150
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Book Description
Sampling is fundamental to nearly every study in the social and policy sciences, yet clear, concise guidance for practitioners and graduate students has been difficult to find. Practical Sampling provides guidance for researchers dealing with the everyday problems of sampling. Using the practical design approach Henry integrates sampling into the overall research design and explains the interrelationships between research design and sampling choices. He lays out alternatives and implications of the choices using four detailed examples to illustrate the alternatives selected and the trade-offs made by applied researchers. The author uses a narrative, conceptual approach throughout the book; mathematical presentations are limited to necessary formulas; and calculations are kept to the absolute minimum, making it an easily approachable book for any researcher, student or professional across the social sciences.
Author: John J. Benedetto
Publisher: Springer Science & Business Media
ISBN: 1461201438
Category : Mathematics
Languages : en
Pages : 423
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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: Peter Tryfos
Publisher: Wiley
ISBN: 9780471047278
Category : Science
Languages : en
Pages : 456
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Book Description
An excellent introductory that uses simple numerical illustrations to provide an intuitive understanding of concepts and confirm major results. Describes various methods for sample selection and estimation including unequal probability sampling and the prediction approach. The accompanying disk contains data files for cases and two computer programs--one of which is an interactive DOS program designed to serve as a tutorial by assisting the implementation of complicated sampling formulas.
Author: Johnnie Daniel
Publisher: SAGE Publications
ISBN: 145222305X
Category : Social Science
Languages : en
Pages : 321
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Book Description
Written for students taking research methods courses, this text provides a thorough overview of sampling principles. The author gives detailed, nontechnical descriptions and guidelines with limited presentation of formulas to help students reach basic research decisions, such as whether to choose a census or a sample, as well as how to select sample size and sample type. Intended for students and researchers in the social and behavioral sciences, public health research, marketing research, and related areas, the text provides nonstatisticians with the concepts and techniques they need to do quality work and make good sampling choices.
Author: S. T. Buckland
Publisher: Springer
ISBN: 3319192191
Category : Medical
Languages : en
Pages : 285
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Book Description
In this book, the authors cover the basic methods and advances within distance sampling that are most valuable to practitioners and in ecology more broadly. This is the fourth book dedicated to distance sampling. In the decade since the last book published, there have been a number of new developments. The intervening years have also shown which advances are of most use. This self-contained book covers topics from the previous publications, while also including recent developments in method, software and application. Distance sampling refers to a suite of methods, including line and point transect sampling, in which animal density or abundance is estimated from a sample of distances to detected individuals. The book illustrates these methods through case studies; data sets and computer code are supplied to readers through the book’s accompanying website. Some of the case studies use the software Distance, while others use R code. The book is in three parts. The first part addresses basic methods, the design of surveys, distance sampling experiments, field methods and data issues. The second part develops a range of modelling approaches for distance sampling data. The third part describes variations in the basic method; discusses special issues that arise when sampling different taxa (songbirds, seabirds, cetaceans, primates, ungulates, butterflies, and plants); considers advances to deal with failures of the key assumptions; and provides a check-list for those conducting surveys.
Author: S. Singh
Publisher: Springer Science & Business Media
ISBN: 9400707894
Category : Medical
Languages : en
Pages : 1242
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Book Description
This book is a multi-purpose document. It can be used as a text by teachers, as a reference manual by researchers, and as a practical guide by statisticians. It covers 1165 references from different research journals through almost 1900 citations across 1194 pages, a large number of complete proofs of theorems, important results such as corollaries, and 324 unsolved exercises from several research papers. It includes 159 solved, data-based, real life numerical examples in disciplines such as Agriculture, Demography, Social Science, Applied Economics, Engineering, Medicine, and Survey Sampling. These solved examples are very useful for an understanding of the applications of advanced sampling theory in our daily life and in diverse fields of science. An additional 173 unsolved practical problems are given at the end of the chapters. University and college professors may find these useful when assigning exercises to students. Each exercise gives exposure to several complete research papers for researchers/students.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
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Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: Baran, Mette L.
Publisher: IGI Global
ISBN: 1522500081
Category : Science
Languages : en
Pages : 362
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Book Description
The clear division between quantitative and qualitative research methods becomes problematic when students begin conducting extensive research for the first time, often as part of a master’s thesis or dissertation. In order to handle such complexities in the selection of research methods, a Mixed Methods Research (MMR) approach is one proposed solution. Mixed Methods Research for Improved Scientific Study seeks to demonstrate how mixed methods research designs can address a wide array of scientific questions across disciplines. Focusing on essential concepts and methods for a hybrid approach to quantitative and qualitative research methods for real-world implementation, this publication is ideally designed for students and researchers interested in refining their research skills as well as educators seeking to integrate research methods coursework into the graduate curriculum.
