A much-needed reference on survey sampling and its applications that presents the latest advances in the field
Seeking to show that sampling theory is a living discipline with a very broad scope, Sampling and Estimation from Finite Populations examines the modern development of the theory 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.
The book 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.
Sampling and Estimation from Finite Populations:

• 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
• Deals with the treatment of non-sampling errors

Sampling and Estimation from Finite Populations is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.