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This book discusses a broad range of statistical design and analysis methods that are particularly well suited to pollution data. It explains key statistical techniques in easy-to-comprehend terms and uses practical examples, exercises, and case studies to illustrate procedures. Dr. Gilbert begins by discussing a space-time framework for sampling pollutants. He then shows how to use statistical sample survey methods to estimate average and total amounts of pollutants in the environment, and how to determine the number of field samples and measurements to collect for this purpose. Then a broad range of statistical analysis methods are described and illustrated. These include: * determining the number of samples needed to find hot spots * analyzing pollution data that are lognormally distributed * testing for trends over time or space * estimating the magnitude of trends * comparing pollution data from two or more populations New areas discussed in this sourcebook include statistical techniques for data that are correlated, reported as less than the measurement detection limit, or obtained from field-composited samples. Nonparametric statistical analysis methods are emphasized since parametric procedures are often not appropriate for pollution data. This book also provides an illustrated comprehensive computer code for nonparametric trend detection and estimation analyses as well as nineteen statistical tables to permit easy application of the discussed statistical techniques. In addition, many publications are cited that deal with the design of pollution studies and the statistical analysis of pollution data. This sourcebook will be a useful tool for applied statisticians, ecologists, radioecologists, hydrologists, biologists, environmental engineers, and other professionals who deal with the collection, analysis, and interpretation of pollution in air, water, and soil.
SRE covers a wide range of environment conditions, facts, and issues from a statistical point of vantage. The major categories (air and water pollution, solid waste generation and management, hazardous wastes and toxic substances) are covered from various perspectives. SRE also assembles information on special problems and wastes (oil spills, global warming, soil erosion), provides profiles of the pollution control industry and legislation, and presents background information of the sort required to place environmental information into a broader context. Thus SRE shows a good deal of data on industrial production in sectors that are major polluters, presents cost and budgetary information, trends in consumption, public opinion, and the like. parag Most of the materials included deal with the environment in North America. Certain subjects, however, such as oil spills and global warming, have an international focus.
Indicators--Air and water -- Climate and weather conditions -- Land and land use -- Wildlife and habitat -- Energy -- Toxic and hazardous substances -- Wastes and resource recovery -- Costs and expenditures -- Markets and companies -- Politics, opinion, law.
Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems. - Includes step-by-step tutorials to aid in understanding the process and implementation of unique data - Presents statistical theory in a simple way without complex mathematical proofs - Shows how to analyze data using R software and provides R scripts for all examples and figures
Data, Statistics, and Useful Numbers for Environmental Sustainability: Bringing the Numbers to Life is an accessible reference for researchers working in environmental and sustainability fields who need to communicate the latest data and statistics to reinforce their own research or message. The book compiles the most-needed numbers into one resource and covers a variety of relevant topics, including materials, energy, environment, city planning, electronics, and waste. This handbook is clearly indexed and full of comprehensive tables, making it easy to find answers. Researchers in environmental and sustainability-related fields will find it an invaluable resource. - Collects and presents important environmental data in one accessible resource - Provides key information needed for effectively communicating environmental and sustainability issues - Offers a clear index - Includes detailed tables throughout for ease of access
The United States is among the wealthiest nations in the world, but it is far from the healthiest. Although life expectancy and survival rates in the United States have improved dramatically over the past century, Americans live shorter lives and experience more injuries and illnesses than people in other high-income countries. The U.S. health disadvantage cannot be attributed solely to the adverse health status of racial or ethnic minorities or poor people: even highly advantaged Americans are in worse health than their counterparts in other, "peer" countries. In light of the new and growing evidence about the U.S. health disadvantage, the National Institutes of Health asked the National Research Council (NRC) and the Institute of Medicine (IOM) to convene a panel of experts to study the issue. The Panel on Understanding Cross-National Health Differences Among High-Income Countries examined whether the U.S. health disadvantage exists across the life span, considered potential explanations, and assessed the larger implications of the findings. U.S. Health in International Perspective presents detailed evidence on the issue, explores the possible explanations for the shorter and less healthy lives of Americans than those of people in comparable countries, and recommends actions by both government and nongovernment agencies and organizations to address the U.S. health disadvantage.
Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Using Statistics to Understand the Environment covers all the basic tests required for environmental practicals and projects and points the way to the more advanced techniques that may be needed in more complex research designs. Following an introduction to project design, the book covers methods to describe data, to examine differences between samples, and to identify relationships and associations between variables. Featuring: worked examples covering a wide range of environmental topics, drawings and icons, chapter summaries, a glossary of statistical terms and a further reading section, this book focuses on the needs of the researcher rather than on the mathematics behind the tests.