Inferential Problems In Survey Sampling

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This book provides a comprehensive account of survey sampling theory in fixed population approach and model based approach. After making a critical review of different results in fixed population set up it shows how superpopulation models can be exploited to produce optimal and robust sampling strategies, specially in large scale sample surveys. The central theme of the book is the use of superpopulation models in making inference from sample surveys. The book also gives suitable emphasis on different practical aspects, like choice of sampling designs, variance estimation, different replication and resampling procedures.The author has taken care to presuppose nothing more on the part of the reader than a first course in statistical inference, sampling theory and regression analysis. He has systematically arranged the main results, supplied short proofs, examples, explanatory notes and remarks and indicated research areas. The book will be very useful to researchers. The survey practitioners will also find some part of the book very helpful.

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Parimal Mukhopadhyay, MSc., PhD, is a member of the faculty of the Indian Statistical Institute, Calcutta, career started in the Bureau of Applied Economics Statistics, WB (196674) and in the Department of Industries, WB (197478) when he was associated with many large scale sample surveys in different responsible capacities. He taught in the University of Ife, Nigeria (198284) and Moi University, Kenya (198990) and visited different universities in US, Canada, Netherlands, Sweden, Thailand, Australia several times as research scientist. He has to his credit one book and more than 50 research papers (some co-authored jointly) in Survey Sampling and Population Mathematics. He has conducted several survey projects at ISI and has been associated with different statistical projects of Government of India at different times.