Sampling and Estimation from Finite Populations

[b]A much-needed reference on survey sampling and its applications that presents the latest advances in the field[/b] Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foundations of survey sampling. It offers readers a critical approach to the subject and discusses putting theory into practice. It also explores the treatment of non-sampling errors featuring a range of topics from the problems of coverage to the treatment of non-response. In addition, the book includes real examples, applications, and a large set of exercises with solutions. [i]Sampling and Estimation from Finite Populations[/i] begins with a look at the history of survey sampling. It then offers chapters on: population, sample, and estimation; simple and systematic designs; stratification; sampling with unequal probabilities; balanced sampling; cluster and two-stage sampling; and other topics on sampling, such as spatial sampling, coordination in repeated surveys, and multiple survey frames. The book also includes sections on: post-stratification and calibration on marginal totals; calibration estimation; estimation of complex parameters; variance estimation by linearization; and much more. Provides an up-to-date review of the theory of sampling Discusses the foundation of inference in survey sampling, in particular, the model-based and design-based frameworks Reviews the problems of application of the theory into practice Also deals with the treatment of non sampling errors [i]Sampling and Estimation from Finite Populations[/i] is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.