Spatial Statistics and Geostatistics

Theory and Applications for Geographic Information Science and Technology

This book is ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice.
Professor Tao Cheng
University College London

This text is a remarkable roadmap to the methods of spatial statistics and in particular, the technique of spatial filtering. The included case studies and computer code make the book extraordinarily interactive and will benefit both students and applied researchers across many disciplines.
W. Ryan Davis
PhD Candidate in Economics, University of Texas at Dallas

This is a valuable and enjoyable addition to applied spatial statistics, particularly because the reader, or rather user, of the book can see exactly what the authors are doing, and so may reproduce all the analyses using the code provided.
Professor Roger S. Bivand
Norges Handelshøyskole Norwegian School of Economics

SAGE has a long tradition of publishing accessible texts explaining key concepts in statistics. This book is in my opinion very useful. I particularly like the choice of statistical problems, the focus on one region to explain a series of problems and the availability of R code, which makes it easy for the reader to reproduce the analysis.

The book is extremely well done, very clear and very helpful, but pretty much advanced. As we are currently developing R skills among students, we are likely to adopt the book in the near future, but for the moment it is too advanced.

Too technical for this level

I quite liked this book and learned some useful things from it. However, it's also rather quirky (eclectic) and not always very clearly written. To me it lacked a clear sense of cohesion or logic to the chapters. Most annoyingly, as far as I can tell the data used in the book are not available anywhere - where to get it isn't mentioned - which renders the R code a bit pointless.

The text is a supplementary reading for social sciences students, since it develops the statistical foundations behind most of the techniques employed in social sciences.

The book spatial statistics and geostatistics is an essential resource for undergraduate and postgraduate students as well as early researcher, because the authors provide a comprehensive overview of spatial statistics and geostatistics. The book provides an excellent overview, supported by excellent examples. A really useful textbook.

The following review regards the book “Statistics for the health sciences a non-mathematical introduction” by Christine P. Dancey, John G. Reidy and Richard Rowe.
There are many textbooks about statistics. The first question we should answer is whether all these books are necessary or not. To my point of view the answer is YES and I will explain why.
Statistic, as many others disciplines, can be approached in several ways and for different “population”. There are texts for beginners, who are commonly afraid of statistic, for students who have average knowledge of the discipline and for advanced ones. In addition some books are focus on particular statistical techniques which are used for ad hoc analysis and are not discussed in essential books. Crossing all the above conditions it would produce a multi dimensions table, with several boxes, each of these “designed” for specific subjects with particular areas of interest, levels of knowledge, approach to the problems, use of tools.
The aim of all the textbooks remain common: to explain the concepts, to support the decision of the readers and to facilitate the interpretation of the results. In other words, making a different example, it is like driving a car: a driver does not need to know how the motor works to drive the car from a place to another. He needs to have a clear idea of the rules of the street, to avoid accident, to know the road to reach the destination, to use the acceleration and the braking pedal etc. Once the driver knows how to drive and the general rules, he does not need to learn it again when he changes the car.
For beginners, especially for those who approach statistic for the first time, or for those who are not very confident with math, it is mainly important to explain the idea of the analysis, clarifying the meaning of an approach instead of another, and only secondly, if it is necessary, to explain the formula which “sustain” the idea. The most important thing is to maintain a clear idea of what to do and how to do. In addition it is useful to provide examples after the notions/concepts are explained.
Statistics for the health sciences a non-mathematical introduction is a book which beginners and intermediate students could find valuable for several reasons:
1) The text maintains what it says in the title “Statistics for the health sciences a non-mathematical introduction”. Beginners will not be afraid of math, in fact, formula are avoided. Readers will be focus on the ideas and on what to do in conducting a correct analysis.
2) The book introduces statistical terms and concepts using common words; moreover it explains how to conduct the analysis, step by step, with the support of pictures taken during the use of SPSS. This statistical software is getting very used not only by professional statistician but also by students who want to conduct some analysis. The program is easy to use because of the possibility to have menu and windows in the selection of the data analysis. The examples presented in the book guide the reader in experiencing, by hand, what it is said in the text, in an efficient way. The reader gets skilled in conducting analysis and becomes more confident with statistic.
3) The book provides also a short introduction of two statistical packages: R and SAS. R is a free statistical software which is getting quite common, especially in those people who are confident with statistic. The attempt of presenting it to beginners could stimulate the interest in those who would like to make a further step in statistic. SAS is a very famous and long traditional statistical software which is normally used by skilled statistician.
4) In the book it is refereed also to external references for specific aspects which are not included in the book but may be useful for those readers who want to experiment other statistical tools.
5) All the chapters have a nice but short overview that makes the readers more confident of what it is expected to find in the following pages. This helps the reader to be more confident in what to focus in reading the chapter.
6) There are many examples taken from the literature. This aspect will prove the readers how useful is statistic in the real world. In addition, the reader will have the possibility to identify, in the examples, similarities with its studies/analysis and to repeat them following the example of the book.
7) In the book there are exercises which can help the student to revise the materials. The online resources, for lecturers and students, expand the concepts treated in the text and provide other useful material for a better understanding.
8) The glossary provides an easy access to definition that sometime can be obscure or cause uncertainly. Readers could benefit from it when they need to revise the definition of a concept, for example when they read a paper and statistical terms are presented.
There are some suggestions which could be useful for improving the book in future revisions:
1) The authors did not mention other statistical programs which are quite common such as Stata and Epinfo. The first one has a large community of users, there are many online resources and textbooks which describe analysis and approach how to use the program. Epiinfo, the latest version is the 7th, can handle basic statistical techniques but has the advantage to be free and it is easy to use. It could be useful to introduce both these programs in the chapter where there Authors presented R and SAS.
2) The authors could introduce how to conduct the analysis using other software, but with the same examples. This would increase the possibility to find readers who could be interested in the book, but have experience with other statistical package.
3) The authors could introduce some summary tables or diagrams for the choice of a technique instead of another. They could draw guided diagrams in which the directions are based on the answers expected by the readers.
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Dr. Gabriele Messina
Research Professor of Public Health
University of Siena