Statistical Framework for Recreational Water Quality Criteria and Monitoring
Statistical Framework for Recreational Water Quality Criteria and Monitoring

Author: Larry J. Wymer

Publisher: John Wiley & Sons

Published: 2007-10-22

Total Pages: 248

ISBN-13: 9780470518311

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With increasing rates of pollution to both land and aquatic environments, regulations for the quality of our waters are necessarily becoming more stringent. In the light of recent epidemiological studies new criteria are being established for the safety of our recreational waters. In order for such criteria to be developed an established statistical framework needs to be in place. Statistical Framework for Recreational Water Quality Criteria and Monitoring offers a practical guide to the statistical methods used for assessing health effects and monitoring and modelling water quality Both traditional and novel sampling designs are discussed. Written by a team of international experts in the field, this book sets out to provide an essential structure for the monitoring of water quality. · Proposes a much-needed framework for the monitoring of water quality, and provides practical guidance on the statistical methods involved. · Covers risk characterization, empirical modelling, sensitivity analysis and measures of robustness. · Details sampling methods and quality control approaches. · Presents crucial, real-life results from recent large-scale studies of water quality, central to the development of the area. · Accompanied by a supplementary website hosting data sets and tools for data analysis. The book is primarily aimed at public health officials, staff of regulatory bodies and students and faculty members of environmental and statistical science courses. There is also much to benefit readers from environmental research and risk analysis.

Guidelines on recreational water quality. Volume 1
Guidelines on recreational water quality. Volume 1

Author: World Health Organization

Publisher: World Health Organization

Published: 2021-07-12

Total Pages: 164

ISBN-13: 9240031308

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Use of coastal, estuarine and freshwater recreational environments has significant benefits for health and well-being, including rest, relaxation, exercise, cultural and religious practices, and aesthetic pleasure, while also providing substantial local, regional and national economic benefits. These guidelines focus on water quality management for coastal and freshwater environments to protect public health. The guidelines: 1. describe the current state of knowledge about the possible adverse health impacts of various forms of water pollution; and2. set out recommendations for setting national health-based targets, conducting surveillance and risk assessments, putting in place systems to monitor and control risks, and providing timely advice to users on water safety.These guidelines are aimed at national and local authorities, and other entities with an obligation to exercise due diligence relating to the safety of recreational water sites. They may be implemented in conjunction with other measures for water safety (such as drowning prevention and sun exposure) and measures for environmental protection of recreational water use sites.

Statistical Monitoring of Complex Multivatiate Processes
Statistical Monitoring of Complex Multivatiate Processes

Author: Uwe Kruger

Publisher: John Wiley & Sons

Published: 2012-08-06

Total Pages: 472

ISBN-13: 1118381262

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The development and application of multivariate statisticaltechniques in process monitoring has gained substantial interestover the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complexsystems, such techniques have been refined and applied in variousengineering areas, for example mechanical and manufacturing,chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statisticaltechniques lies in its simplicity and adaptability for developingmonitoring applications. In contrast, competitive model,signal or knowledge based techniques showed their potential onlywhenever cost-benefit economics have justified the required effortin developing applications. Statistical Monitoring of Complex Multivariate Processespresents recent advances in statistics based process monitoring,explaining how these processes can now be used in areas such asmechanical and manufacturing engineering for example, in additionto the traditional chemical industry. This book: Contains a detailed theoretical background of the componenttechnology. Brings together a large body of work to address thefield’s drawbacks, and develops methods for theirimprovement. Details cross-disciplinary utilization, exemplified by examplesin chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outliningdeficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homeworkassignments in the form of individual and team-based projects, toenhance the learning experience. Features a supplementary website including Matlab algorithmsand data sets. This book provides a timely reference text to the rapidlyevolving area of multivariate statistical analysis for academics,advanced level students, and practitioners alike.

Statistical Methods for Hospital Monitoring with R
Statistical Methods for Hospital Monitoring with R

Author: Anthony Morton

Publisher: John Wiley & Sons

Published: 2013-06-27

Total Pages: 462

ISBN-13: 1118639170

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Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: Provides functions to perform quality improvement and infection management data analysis. Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events. Provides a summary of key non-statistical aspects of hospital safety and easy to use functions. Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.

Introduction to Probability and Statistics for Ecosystem Managers
Introduction to Probability and Statistics for Ecosystem Managers

Author: Timothy C. Haas

Publisher: John Wiley & Sons

Published: 2013-05-21

Total Pages: 271

ISBN-13: 1118636236

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Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self-contained introduction for individuals involved in monitoring, assessing, and managing ecosystems and features intuitive, simulation-based explanations of probabilistic and statistical concepts. Mathematical programming details are provided for estimating ecosystem model parameters with Minimum Distance, a robust and computer-intensive method. The majority of examples illustrate how probability and statistics can be applied to ecosystem management challenges. There are over 50 exercises – making this book suitable for a lecture course in a natural resource and/or wildlife management department, or as the main text in a program of self-study. Key features: Reviews different approaches to wildlife and ecosystem management and inference. Uses simulation as an accessible way to explain probability and stochastic model behavior to beginners. Covers material from basic probability through to hierarchical Bayesian models and spatial/ spatio-temporal statistical inference. Provides detailed instructions for using R, along with complete R programs to recreate the output of the many examples presented. Provides an introduction to Geographic Information Systems (GIS) along with examples from Quantum GIS, a free GIS software package. A companion website featuring all R code and data used throughout the book. Solutions to all exercises are presented along with an online intelligent tutoring system that supports readers who are using the book for self-study.

Statistical Methods for Evaluating Safety in Medical Product Development
Statistical Methods for Evaluating Safety in Medical Product Development

Author: A. Lawrence Gould

Publisher: John Wiley & Sons

Published: 2014-12-08

Total Pages: 390

ISBN-13: 1118763106

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This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

Author: Richard Chandler

Publisher: John Wiley & Sons

Published: 2011-03-25

Total Pages: 348

ISBN-13: 111999196X

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The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

Statistical DNA Forensics
Statistical DNA Forensics

Author: Wing Kam Fung

Publisher: John Wiley & Sons

Published: 2008-04-15

Total Pages: 262

ISBN-13: 9780470727034

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Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence. This book presents the methodology of statistical DNA forensics with an emphasis on the use of computational techniques to analyze and interpret forensic evidence.

Crossover Designs
Crossover Designs

Author: Kung-Jong Lui

Publisher: John Wiley & Sons

Published: 2016-08-08

Total Pages: 248

ISBN-13: 1119114691

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A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible. As evidenced by extensive research publications, crossover design can be a useful and powerful tool to reduce the number of patients needed for a parallel group design in studying treatments for non-curable chronic diseases. This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design. Key features: Provides exact test procedures and interval estimators, which are especially of use in small-sample cases. Presents most test procedures and interval estimators in closed-forms, enabling readers to calculate them by use of a pocket calculator or commonly-used statistical packages. Each chapter is self-contained, allowing the book to be used a reference resource. Uses real-life examples to illustrate the practical use of test procedures and estimators Provides extensive exercises to help readers appreciate the underlying theory, learn other relevant test procedures and understand how to calculate the required sample size. Crossover Designs: Testing, Estimation and Sample Size will be a useful resource for researchers from biostatistics, as well as pharmaceutical and clinical sciences. It can also be used as a textbook or reference for graduate students studying clinical experiments.

Quality of Life Outcomes in Clinical Trials and Health-Care Evaluation
Quality of Life Outcomes in Clinical Trials and Health-Care Evaluation

Author: Stephen J. Walters

Publisher: John Wiley & Sons

Published: 2009-09-10

Total Pages: 380

ISBN-13: 9780470871911

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An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials. Quality of Life (QoL) outcomes or Person/Patient Reported Outcome Measures (PROMs) are now frequently being used in randomised controlled trials (RCTs) and observational studies. This book provides a practical guide to the design, analysis and interpretation of studies that use such outcomes. QoL outcomes tend to generate data with discrete, bounded and skewed distributions. Many investigators are concerned about the appropriateness of using standard statistical methods to analyse QoL data and want guidance on what methods to use. QoL outcomes are frequently used in cross-sectional surveys and non-randomised health-care evaluations. Provides a user-friendly guide to the design and analysis of clinical trials and observational studies in relation to QoL outcomes. Discusses the problems caused by QoL outcomes and presents intervention options to help tackle them. Guides the reader step-by-step through the selection of appropriate QoLs. Features exercises and solutions and a supporting website providing downloadable data files. Illustrated throughout with examples and case studies drawn from the author’s experience, this book offers statisticians and clinicians guidance on choosing between the numerous available QoL instruments.