Bikas K. Sinha – författare
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8 produkter
8 produkter
539 kr
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This book is a follow up of "Theory of Optimal Designs" by K.R. Shah and Bikas K. Sinha published in this series. Unlike the previous book, this one covers a wide range of topics in both discrete and continuous optimal designs. The topics discussed include designs for regression models, covariates models, models with trend effects, and models with competition effects. An extensive study on a new optimality criterion is also presented. The prerequisites are a basic course in the design and analysis of experiments and some familiarity with the concepts of optimality criteria. Erkki P. Liski is Professor of Statistics at the University of Tampere in Finland. He has been head of various research projects on theory and applications of statistics with the Academy of Finland. Nripes K. Mandal is Professor of Statistics at Calcutta University in India. He is closely associated with all academic activities of the Calcutta Statistical Association. Kirti R. Shah is Professor of Statistics at the University of Waterloo in Canada. He is currently the president of the International Indian Statistical Association. Bikas K.Sinha is Professor of Statistics at the Indian Statistical Institute in Calcutta, India. He has served on the editorial board of a number of international statistical journals.
Del 64 - Wiley Series in Survey Methodology
Design and Inference in Finite Population Sampling
Inbunden, Engelska, 1991
3 222 kr
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Covers a new but essential development in the field of population sampling, namely inference in finite sampling. Offers some important topics not found in other texts on sampling such as the superpopulation approach and randomized response, nonresponse and resampling techniques.
2 304 kr
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Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks.
Intended Audience This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences
1 178 kr
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This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.
858 kr
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This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research.
- Nyhet
602 kr
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1 174 kr
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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).
856 kr
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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.