Walter W. Piegorsch

A. John Bailer

Environmental statistics is a rapidly growing field, supported by advances in digital computing power, automated data collection systems, and interactive, linkable Internet software. Concerns over public and ecological health and the continuing need to support environmental policy-making and regulation have driven a concurrent explosion in environmental data analysis. This textbook is designed to address the need for trained professionals in this area. The book is based on a course which the authors have taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of data evaluation. The text extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses. In particular, it: Provides a coherent introduction to intermediate and advanced methods for modeling and analyzing environmental data. Takes a data-oriented approach to describing the various methods. Illustrates the methods with real-world examples Features extensive exercises, enabling use as a course text. Includes examples of SAS computer code for implementation of the statistical methods. Connects to a Web site featuring solutions to exercises, extra computer code, and additional material. Serves as an overview of methods for analyzing environmental data, enabling use as a reference text for environmental science professionals. Graduate students of statistics studying environmental data analysis will find this invaluable as will practicing data analysts and environmental scientists including specialists in atmospheric science, biology and biomedicine, chemistry, ecology, environmental health, geography, and geology.

Analyzing Environmental Data

Hao Helen Zhang

Richard A. Levine

Thomas C. M. Lee

Ein unverzichtbarer Leitfaden bei der Anwendung computergestützter Statistik in der modernen Datenwissenschaft In Computational Statistics in Data Science präsentiert ein Team aus bekannten Mathematikern und Statistikern eine fundierte Zusammenstellung von Konzepten, Theorien, Techniken und Praktiken der computergestützten Statistik für ein Publikum, das auf der Suche nach einem einzigen, umfassenden Referenzwerk für Statistik in der modernen Datenwissenschaft ist. Das Buch enthält etliche Kapitel zu den wesentlichen konkreten Bereichen der computergestützten Statistik, in denen modernste Techniken zeitgemäß und verständlich dargestellt werden. Darüber hinaus bietet Computational Statistics in Data Science einen kostenlosen Zugang zu den fertigen Einträgen im Online-Nachschlagewerk Wiley StatsRef: Statistics Reference Online. Außerdem erhalten die Leserinnen und Leser: * Eine gründliche Einführung in die computergestützte Statistik mit relevanten und verständlichen Informationen für Anwender und Forscher in verschiedenen datenintensiven Bereichen * Umfassende Erläuterungen zu aktuellen Themen in der Statistik, darunter Big Data, Datenstromverarbeitung, quantitative Visualisierung und Deep Learning Das Werk eignet sich perfekt für Forscher und Wissenschaftler sämtlicher Fachbereiche, die Techniken der computergestützten Statistik auf einem gehobenen oder fortgeschrittenen Niveau anwenden müssen. Zudem gehört Computational Statistics in Data Science in das Bücherregal von Wissenschaftlern, die sich mit der Erforschung und Entwicklung von Techniken der computergestützten Statistik und statistischen Grafiken beschäftigen.

Computational Statistics in Data Science

Mark M. Smith

Susan Cutter

Christopher T. Emrich

Jerry T. Mitchell

Lynn Weber

Hurricane Katrina slammed into the Gulf Coast in August 2005 with devastating consequences. Almost all analyses of the disaster have been dedicated to the way the hurricane affected New Orleans. This volume examines the impact of Katrina on southern Mississippi. While communities along Mississippi's Gulf Coast shared the impact, their socioeconomic and demographic compositions varied widely, leading to different types and rates of recovery. This volume furthers our understanding of the pace of recovery and its geographic extent, and explores the role of inequalities in the recovery process and those antecedent conditions that could give rise to a 'recovery divide'. It will be especially appealing to researchers and advanced students of natural disasters and policy makers dealing with disaster consequences and recovery.

Hurricane Katrina and the Forgotten Coast of Mississippi

Douglas Nychka

Lawrence H. Cox

This book offers a set of case studies exemplifying the broad range of statis tical science used in environmental studies and application. The case studies can be used for graduate courses in environmental statistics, as a resource for courses in statistics using genuine examples to illustrate statistical methodol ogy and theory, and for courses in environmental science. Not only are these studies valuable for teaching about an essential cross-disciplinary activity but they can also be used to spur new research along directions exposed in these examples. The studies reported here resulted from a program of research carried on by the National Institute of Statistical Sciences (NISS) during the years 1992- 1996. NISS was created in 1991 as an initiative of the national statistics or ganizations, with the mission to renew and focus efforts of statistical science on important cross-disciplinary problems. One of NISS' first projects was a cooperative research effort with the U.S. Environmental Protection Agency (EPA) on problems of great interest to environmental science and regulation, surely one of today's most important cross-disciplinary activities. With the support and encouragement of Gary Foley, Director of the (then) U.S. EPA Atmospheric Research and Exposure Assessment Laboratory, a project and a research team were assembled by NISS that pursued a program which produced a set of results and products from which this book was drawn.

Case Studies in Environmental Statistics

Hurricane Katrina slammed into the Gulf Coast in August 2005 with devastating consequences. Almost all analyses of the disaster have been dedicated to the way the hurricane affected New Orleans. This volume examines the impact of Katrina on southern Mississippi. While communities along Mississippi's Gulf Coast shared the impact, their socioeconomic and demographic compositions varied widely, leading to different types and rates of recovery. This volume furthers our understanding of the pace of recovery and its geographic extent, and explores the role of inequalities in the recovery process and those antecedent conditions that could give rise to a "recovery divide." It will be especially appealing to researchers and advanced students of natural disasters and policy makers dealing with disaster consequences and recovery.

Walter W. Piegorsch

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