Sampling Statistics

Discover the latest developments and current practices in survey
sampling

Survey sampling is an important component of research in many
fields, and as the importance of survey sampling continues to grow,
sophisticated sampling techniques that are both economical and
scientifically reliable are essential to planning statistical
research and the design of experiments. Sampling Statistics
presents estimation techniques and sampling concepts to facilitate
the application of model-based procedures to survey samples.

The book begins with an introduction to standard probability
sampling concepts, which provides the foundation for studying
samples selected from a finite population. The development of the
theory of complex sampling methods is detailed, and subsequent
chapters explore the construction of estimators, sample design,
replication variance estimation, and procedures such as nonresponse
adjustment and small area estimation where models play a key role.
A final chapter covers analytic studies in which survey data are
used for the estimation of parameters for a subject matter
model.

The author draws upon his extensive experience with survey
samples in the book's numerous examples. Both the production of
"general use" databases and the analytic study of a limited number
of characteristics are discussed. Exercises at the end of each
chapter allow readers to test their comprehension of the presented
concepts and techniques, and the references provide further
resources for study.

Sampling Statistics is an ideal book for courses in
survey sampling at the graduate level. It is also a valuable
reference for practicing statisticians who analyze survey data or
are involved in the design of sample surveys.