The first chapter of the book introduces to the reader basic concepts of Sampling
Theory which are essential to understand the later chapters. Some numerical
examples are also presented to help the readers to have clear understanding of
the concepts. Simple random sampling design is dealt with in detail in the
second chapter. Several solved examples which consider various competing
estimators for the population total are also included in the same chapter. The
third is devoted to systematic sampling schemes. Various systematic sampling
schemes like, linear, circular, balanced, modified systematic sampling and their
performances under different superpopulation models are also discussed. In the
fourth chapter several unequal probability sampling-estimating strategies are
presented. Probability Proportional to Size Sampling With and Without
Replacement are considered with appropriate estimators. In addition to them
Midzuno sampling scheme and Random group Method are also included.
Stratified sampling, allocation problems and related issues are presented with
full details in the fifth chapter. Many interesting solved problems are also added.
In the sixth and seventh chapters the use of auxiliary information in ratio and
regression estimation are discussed. Results related to the properties of ratio and
regression estimators under super-population models are also given. Cluster
sampling and Multistage sampling are presented in the eighth chapter. The
results presented in under two stage sampling are general in nature. In the ninth
chapter, non-sampling errors, randomised response techniques and related topics
are discussed. Some recent developments in Sample surveys namely, Estimation
of distribution functions, Adaptive sampling schemes, Randomised response
methods for quantitative data are presented in the tenth chapter.