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Visualizing Data Patterns with Micromaps : Chapman & Hall/CRC Interdisciplinary Statistics - Daniel B. Carr

Visualizing Data Patterns with Micromaps

By: Daniel B. Carr, Linda Williams Pickle

Hardcover | 29 April 2010 | Edition Number 1

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"The book is extremely well written. I was totally absorbed by chapters one through four. It is obvious that the authors are in total command of the topic and bring years of experience in the field to the project. The authors understand what areas need special attention and explanation. The language flows nicely and the text is illustrative and entertaining. The limitations of micromaps are known and discussed. The reader gains a good understanding of what they are for and what they can and cannot accomplish.---Oliver Schabenberger, SAS Institute Inc., Cary, North Carolina, USA

This is a terrific book and it introduces some clever tools."---David Berrigan, NIH/NCI

Bringing together the research of two leaders in this field, Visualizing Data Patterns with Micromaps presents the many design variations and applications of micromaps, which link statistical information to an organized set of small maps. After illustrating the three main types of micromaps, the authors summarize the research behind the design of visualization tools that support exploration and communication of spatial data patterns. They then explain how these research findings can be applied to micromap designs in general and detail the specifics involved with linked, conditioned, and comparative micromap designs. To compare and contrast their purposes, limitations, and strengths, the final chapter applies all three of these techniques to the same demographic data for Louisiana before and after Hurricanes Katrina and Rita.

Showing how to bring statistics to life, this full-color book helps readers simultaneously explore the statistical geographic patterns in their data. The supplementary website provides many resources, including boundary files, real-world data sets, Java-based CCmaps for conditioned micromaps, and R functions and scripts for linked and comparative micromaps.
Industry Reviews
The book is well-written and nicely organized ! Overall, I found the book is well-researched and informative. It uses lucid and easy-to-understand language. Additionally, the book contains numerous colorful micromap variations that visually illustrate design principles and real-world applications. It clearly shows the authors' enthusiasm for micromaps and their deep knowledge of the subject. ! I highly recommend this book for a diverse audience who are interested in exploring and presenting their data in a joint statistical and spatial context. ! an excellent text for graduate courses in data visualization. The authors clearly succeeded in making this book suitable for teaching by providing both theoretical foundations and practical examples for designing effective visualization tools. An attractive feature of the book is that it has a companion website ! I congratulate the authors for this great book. It will be an excellent addition to the data visualization literature and I will definitely use it as my reference. --Samson Y. Gebreab, The American Statistician, August 2011 [M]icromaps are an effective tool and the book explains them at length, with lots of examples, so that non-statisticians can understand and use them. ! the graphic displays in this book are clear and straightforward ! --International Statistical Review, 2011 The book is extremely well written. I was totally absorbed by chapters one through four. It is obvious that the authors are in total command of the topic and bring years of experience in the field to the project. The authors understand what areas need special attention and explanation. The language flows nicely and the text is illustrative and entertaining. The limitations of micromaps are known and discussed. The reader gains a good understanding of what they are for and what they can and cannot accomplish. --Oliver Schabenberger, SAS Institute Inc., Cary, North Carolina, USA This is a terrific book and it introduces some clever tools. --David Berrigan, NIH/NCI

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