Sampling / Edition 2

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Overview

From the reviews of the First Edition:
"A well-written book that deserves to be widely used, both by statistics teachers and by researchers."
-Biometrics
"The explanations are clear and concise, the presentation is extremely pleasing, the references are up to date, and there is an abundance of examples."
-Short Book Reviews
"This is a highly recommended acquisition for any statistician concerned with the collection of sample information."
-Technometrics
All aspects of obtaining, interpreting, and using sample data in a new revised volume
Sampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. 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 such as methods that combine design and model-based approaches, adjusting for nonsampling errors, and the use of link-tracing designs. 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.
Featuring a wider range of topics than other sampling books, Sampling, Second Edition is the ideal reference for scientific researchers and other professionals who use sampling, as well as students in sampling courses.
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Editorial Reviews

From the Publisher
"This is an informative and clearly written book that will serve as a useful reference for researchers and as an introduction for students…" (Statistics in Medical Research, October 2005)

"...treats both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations." (SciTech Book News, Vol. 26, No. 2, June 2002)

"...a well-written and expanded new edition...an excellent book on an important subject. Highly recommended..." (Choice, Vol. 40, No. 2, October 2002)

"This book has never had a competitor. It is the only book that takes a broad approach to sampling...any good personal statistics library should include a copy of this book." (Technometrics, Vol. 44, No. 4, November 2002)

"...an ideal reference for scientific researchers and other professionals who use sampling..."(Zentralblatt Math, Vol.1002, No.02, 2003)

From The Critics
This text treats both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This second edition includes descriptions of new developments in the field, a wider range of approaches to common problems, historical notes, and increased coverage of adjusting for nonsampling errors, the use of link-tracing designs, and of methods combining design and model-based approaches. Material is updated to show how sampling methods function in such fields as the biological, environmental, social, and health sciences, and with new material on sampling the Internet. Thompson teaches statistics at the Pennsylvania State University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Booknews
A textbook for a graduate or upper-level undergraduate course in sampling. Describes advanced methods by which researchers can pursue difficult sampling problems, such as counting an elusive human or animal population, predicting the amount of fossil-fuel resource at a new site, or estimating the prevalence of a rare disease. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780471291169
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 1/28/2002
  • Series: Wiley Series in Probability and Statistics Series , #404
  • Edition description: REV
  • Edition number: 2
  • Pages: 400
  • Product dimensions: 6.46 (w) x 9.27 (h) x 1.06 (d)

Meet the Author

STEVEN K. THOMPSON, PhD, is Professor of Statistics at the Pennsylvania State University. During his career he has served on the faculties of the University of Auckland and the University of Alaska. He is the author of Adaptive Sampling (with George Seber), also published by Wiley.
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Table of Contents

Preface to the Second Edition.

Preface to the First Edition.

1. Introduction.

PART I: BASIC SAMPLING.

2. Simple Random Sampling.

3. Confidence Intervals.

4. Sample Size.

5. Estimating Proportions, Ratios, and Subpopulation Means.

6. Unequal Probability Sampling.

PART II: MAKING THE BEST USE OF SURVEY DATA.

7. Auxiliary Data and Ratio Estimation.

8. Regression Estimation.

9. The Sufficient Statistic in Sampling.

10. Design and Model.

PART III SOME USEFUL DESIGNS.

11. Stratified Sampling.

12. Cluster and Systematic Sampling.

13. Multistage Designs.

14. Double or Two-Phase Sampling.

PART IV METHODS FOR ELUSIVE AND HARD-TO-DETECT POPULATIONS.

15. Network Sampling and Link-Tracing Designs.

16. Detectability and Sampling.

17. Line and Point Transects.

18. Capture-Recapture Sampling.

19. Line-Intercept Sampling.

PART V SPATIAL SAMPLING.

20. Spatial Prediction or Kriging.

21. Spatial Designs.

22. Plot Shapes and Observational Methods.

PART VI ADAPTIVE SAMPLING.

23. Adaptive Sampling Designs.

24. Adaptive Cluster Sampling.

25. Systematic and Strip Adaptive Cluster Sampling.

26. Stratified Adaptive Cluster Sampling.

Answers to Selected Exercises.

References.

Author Index.

Subject Index.

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