Sampling Techniques

Sampling techniques have been widely used in almost all areas of life. The method of drawing a sample is very important for estimation of population characteristics. In this book we have made an attempt to discuss popular sampling designs and estimation methods that can be used for estimation of population characteristics. This book presents two popular sampling design categories, namely the sampling of units and the sampling of groups of units. We have discussed designs that can be...
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Sampling techniques have been widely used in almost all areas of life. The method of drawing a sample is very important for estimation of population characteristics. In this book we have made an attempt to discuss popular sampling designs and estimation methods that can be used for estimation of population characteristics. This book presents two popular sampling design categories, namely the sampling of units and the sampling of groups of units. We have discussed designs that can be used for the sampling of units (for example, simple random sampling) and designs that are used for the sampling of groups (for example, cluster and multistage sampling). The availability of supplementary information provides a basis to improve the efficiency of estimates. This book discusses estimation methods with and without the use of supplementary information. Two popular methods which use supplementary information - namely, ratio and regression estimators - have been discussed in detail in this book alongside their design and model based study. The probabilities of population unit selection plays an important role in estimation. In this regard, the sampling designs are classified into two broader categories, namely equal probability sampling and unequal probability sampling. This book discusses in detail both of these sampling designs. The unequal probability sampling design has been discussed in the context of the Hansen-Hurwitz (1943) estimator, Horvitz-Thompson (1952) estimator and some special estimators. The model based study of various estimators provides insight about their behavior under a linear stochastic model. This book provides a detailed discussion about properties of various estimators under a linear stochastic model both in equal and unequal probability sampling. Finally, the book presents useful material on multiphase sampling. This book can be effectively used at undergraduate and graduate levels. The book is helpful for research students who want to pursue their career in sampling. The book is also helpful for practitioners to know the application of various sampling designs and estimators. "