Sampling

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.

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.

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.

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.

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.

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.

Item came as described and delivered quickly.

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

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.