Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses. The book contains a Preface, Acknowledgements and 18 chapters divided over four parts. Chapter 1: An Overview of Sample Design and Weighting, is followed by Part 1: "Designing Single-Stage Sample Surveys" with Chapter 2: Project 1: Design a Single-Stage Personnel Survey; Chapter 3: Sample Design and Sample Size for Single-Stage Surveys; Chapter 4: Power Calculations and Sample Size Determination; Chapter 5: Mathematical Programming; Chapter 6: Outcome Rates and Effect on Sample Size; and Chapter 7: The Personnel Survey Design Project: One Solution. Part II: "Multistage Designs" includes Chapter 8: Project 2: Designing an Area Sample; Chapter 9: Designing Multistage Samples; Chapter 10: Area Sampling; and Chapter 11: The Area Sample Design: One Solution. Part III:" Survey Weights and Analyses" follows with Chapter 12: Project 3: Weighting a Personnel Survey; Chapter 13: Basic Steps in Weighting; Chapter 14: Calibration and Other Uses of Auxiliary Data; Chapter 15: Variance Estimation, and Chapter 16: Weighting the Personnel Survey: One Solution. Part IV: "Other Topics" follows with Chapter 17: Multiphase Designs; and Chapter 18: Process Control and Quality Measures. Appended are: (1) Notation Glossary; (2) Data Sets; and (3) R Functions Used in this Book. Also included are References, Solutions to Selected Exercises, an Author Index, and a Subject Index.