Sampling 3rd Edition by Steven K. Thompson (PDF)

Description

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 MathFeatures new developments in the field combined with all aspects of obtaining, interpreting, and using sample dataSampling 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.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐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.

⭐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.

⭐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.

⭐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.

⭐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.

⭐Item came as described and delivered quickly.

⭐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.

⭐Great book — very user friendly, has exercises with some answers in the back. I wouldl recommend to anyone learning sampling.

⭐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.

⭐you need to plan a sample based study? this book may help you.

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