Covering both classical and modern sampling methods, this volume pays special attention to techniques of sampling and estimation for populations which are inherently difficult to estimate. The text demonstrates how to use methods to develop effective sampling designs for real life situations.
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Covers both classical and modern sampling design and estimation methods, focusing on methods for populations that are difficult to sample--elusive, rare, clustered or hard to detect. Divided into six parts, it covers basic sampling from simple random to unequal probability sampling; treats the use of auxiliary data with ratio and regression estimation and looks at the ideas of sufficient data and of model and design in practical sampling; discusses major useful designs, including stratified, cluster, systematic, multi-stage, double and network sampling; examines detectability methods for elusive populations; explains spatial sampling; and introduces adaptive sampling designs. Each chapter contains exercises with answers provided in the appendix.
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