Sampling provides an overview of classical and modern sampling design and estimation methods. This Second Edition's extensive new material includes descriptions of new developments, a wider range of approaches to common problems, historical notes, and increased coverage of topics. Updated chapters show how relevant sampling methods function within such fields as the biological, environmental, and geological sciences; social and health sciences; and sampling the Internet. Organized into six sections, this edition covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio estimators and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Additional derivations, notes on underlying ideas, exercises, and examples foster a greater mastery of the presented techniques. New numerical examples, small-population examples, and exercises have been added.