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