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This full-color book explores the design variations and applications of micromaps, which link statistical information to an organized set of small maps. It illustrates the three main types of micromaps (linked, conditioned, and comparative) and summarizes the cognitive research and statistical thinking behind these designs. The book then explains the specific design elements and applications of each of the main 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…mehr

Produktbeschreibung
This full-color book explores the design variations and applications of micromaps, which link statistical information to an organized set of small maps. It illustrates the three main types of micromaps (linked, conditioned, and comparative) and summarizes the cognitive research and statistical thinking behind these designs. The book then explains the specific design elements and applications of each of the main 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. Many supplementary resources are available on the book's website.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Daniel B. Carr is Professor of Statistics at George Mason University in Fairfax, Virginia. Building on his early experience in developing static and dynamic graphics at Pacific Northwest National Laboratory, Dr. Carr continues to use new data as the motivation to create new graphics. He has taught statistical graphics to hundreds of graduate students in the computational data sciences. For more than 30 years, he has developed graphical and computational methods for exploratory visualization and has collaborated with researchers at several federal agencies, including working with Dr. Pickle at the National Cancer Institute (NCI). Dr. Carr is a Fellow of the American Statistical Association.

Linda Williams Pickle is principal and chief statistician at StatNet Consulting, LLC in Gaithersburg, Maryland, and Adjunct Professor of Geography and Public Health Services at Pennsylvania State University. She has devoted more than 30 years to the cancer research community, working for the National Cancer Institute (NCI), the Vincent T. Lombardi Comprehensive Cancer Center at Georgetown University, and the National Center for Health Statistics (NCHS). Dr. Pickle has published extensively about the spatial patterns of disease, including the award-winning Atlas of United States Mortality, which was the first of its kind to use statistical modeling in the background and to produce age-specific mortality rates based on modeled data. She is a Fellow of the American Statistical Association.