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Sampling 3rd Edition, Kindle Edition

3.8 3.8 out of 5 stars 21 ratings

Praise for the Second Edition

"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

"Well-written . . . an excellent book on an important subject. Highly recommended."
Choice

"An ideal reference for scientific researchers and other professionals who use sampling."
Zentralblatt Math

Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data

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 Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more.

Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio 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.

Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.

Due to its large file size, this book may take longer to download

Editorial Reviews

From the Inside Flap

Praise for the Second Edition

 

"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

"Well-written . . . an excellent book on an important subject. Highly recommended." —Choice

"An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math

Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data

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 Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more.

Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio 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.

Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.

From the Back Cover

Praise for the Second Edition

"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

"Well-written . . . an excellent book on an important subject. Highly recommended." ―Choice

"An ideal reference for scientific researchers and other professionals who use sampling." ―Zentralblatt Math

Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data

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 Third Edition retains the general organization of the two previous editions, but incorporates extensive new material―sections, exercises, and examples―throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more.

Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio 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.

Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.

Product details

  • ASIN ‏ : ‎ B0078XBZ6K
  • Publisher ‏ : ‎ Wiley; 3rd edition (February 8, 2012)
  • Publication date ‏ : ‎ February 8, 2012
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 24801 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Sticky notes ‏ : ‎ On Kindle Scribe
  • Print length ‏ : ‎ 469 pages
  • Customer Reviews:
    3.8 3.8 out of 5 stars 21 ratings

About the author

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Steven K. Thompson
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Customer reviews

3.8 out of 5 stars
3.8 out of 5
21 global ratings

Customers say

Customers find the book a good reference for sampling approaches and easy to understand. They also appreciate the good R examples with each chapter.

AI-generated from the text of customer reviews

6 customers mention "Sampling approaches"6 positive0 negative

Customers find the book on sampling approaches to be a good reference. They also say it's useful for more advanced methods and has exercises with some answers in the back.

"It is a very good book, but not stand-alone. I recently taught with this textbook for a graduate research design course for the social sciences...." Read more

"Great book on sampling approaches... would be 5 stars if there were not so many mistakes in the formulas in text!..." Read more

"Great book -- very user friendly, has exercises with some answers in the back. I wouldl recommend to anyone learning sampling." Read more

"Great reference and easy to understand. Must have for any stats major! Good R examples with each chapter. Highly recommend!" Read more

5 customers mention "Comprehensibility"5 positive0 negative

Customers find the book easy to understand, clear on information, and accessible. They also appreciate the good R examples with each chapter.

"...the different types of sampling are helpful, and the code is understandable to someone who isn't a complete expert at R. The examples help reinforce..." Read more

"...I love this book. It's concise, consistent, and accessible. It really feels like the author put a solid effort into every single section...." Read more

"The book is pretty clear on information and very easy to follow." Read more

"Great book -- very user friendly, has exercises with some answers in the back. I wouldl recommend to anyone learning sampling." Read more

Top reviews from the United States

Reviewed in the United States on June 26, 2020
This is a book about different types of sampling. It tells you how to do calculations related to simple random sampling, unequal probability sampling, stratified sampling, cluster and systematic sampling, and multistage designs. The diagrams for describing the different types of sampling are helpful, and the code is understandable to someone who isn't a complete expert at R. The examples help reinforce the material in the book. I am about to use this book for a graduate level class.
Reviewed in the United States on March 2, 2012
It is a very good book, but not stand-alone. I recently taught with this textbook for a graduate research design course for the social sciences. I felt that it's introduction to the basics of sampling theory and randomization inference were overly concise to the point of obscuring important points for students coming to this material for the first time. So, I had to use Cochran's Sampling Techniques for that material. Cochran's treatment remains the most lucid. Then, with Cochran's foundation the latter portions of Thompson's book were a great read, especially his extended analysis of designs for rare and hidden populations -- something of particular interest in social science.
11 people found this helpful
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Reviewed in the United States on September 11, 2014
I'm a grad student in computer science. I love this book. It's concise, consistent, and accessible. It really feels like the author put a solid effort into every single section. The chapter and overal structure is also logical and easy to follow. I'm readying this book cover to cover.
2 people found this helpful
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Reviewed in the United States on March 13, 2020
I own the print and Kindle versions of the 3rd edition.

The are mathematical symbols that fail to translate from print to the Kindle edition. One obvious example is \bar{M} translates as "M". In a nutshell, this happens so often that the Kindle should come with a warning and discounted price!

Note that the errors I describe go beyond those in the print edition.
One person found this helpful
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Reviewed in the United States on February 20, 2017
Great book on sampling approaches... would be 5 stars if there were not so many mistakes in the formulas in text! You'd think they would have caught all of those by the 3rd edition. Still a good reference, just be sure to read carefully so as to catch and correct errors.
2 people found this helpful
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Reviewed in the United States on February 25, 2018
Tons of errors! How is this a third edition???!!?? It was required for my class and this is one book I won't be keeping around for reference.
2 people found this helpful
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Reviewed in the United States on December 30, 2019
Item came as described and delivered quickly.
Reviewed in the United States on September 8, 2014
The book is pretty clear on information and very easy to follow.

Top reviews from other countries

Concobus
3.0 out of 5 stars Not great
Reviewed in Canada on February 18, 2019
Overall, this is not a horrible text but it is often concise to the point of not being helpful and contains numerous typos/errors. The R code is clumsy and not "R-like" (e.g., the use of for loops rather than replicate()), terribly documented so it is difficult to tell what is being done at each step and why, and the code contains a number of errors that prevent it from running.

Given the high price for such a small book and its intended use as a reference text, it is unfortunate/shameful that there are no errata available for this textbook online.
One person found this helpful
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Immo
4.0 out of 5 stars all about sampling
Reviewed in Germany on February 16, 2020
you need to plan a sample based study? this book may help you.

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