Basic Statistical Tools for Improving Quality

The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This second edition of Statistical Methods for Food Science provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands-on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level. This revised and updated second edition is accompanied by a new companion website giving the reader access to the datasets and Excel spreadsheets featured in the book. Check it out now by visiting www.wiley.com/go/bower/statistical or by scanning the QR code below.

Integrate critical roles to improve overall performance in complex engineering projects Integrating Program Management and Systems Engineering shows how organizations can become more effective, more efficient, and more responsive, and enjoy better performance outcomes. The discussion begins with an overview of key concepts, and details the challenges faced by System Engineering and Program Management practitioners every day. The practical framework that follows describes how the roles can be integrated successfully to streamline project workflow, with a catalog of tools for assessing and deploying best practices. Case studies detail how real-world companies have successfully implemented the framework to improve cost, schedule, and technical performance, and coverage of risk management throughout helps you ensure the success of your organization's own integration strategy. Available course outlines and PowerPoint slides bring this book directly into the academic or corporate classroom, and the discussion's practical emphasis provides a direct path to implementation. The integration of management and technical work paves the way for smoother projects and more positive outcomes. This book describes the integrated goal, and provides a clear framework for successful transition. Overcome challenges and improve cost, schedule, and technical performance Assess current capabilities and build to the level your organization needs Manage risk throughout all stages of integration and performance improvement Deploy best practices for teams and systems using the most effective tools Complex engineering systems are prone to budget slips, scheduling errors, and a variety of challenges that affect the final outcome. These challenges are a sign of failure on the part of both management and technical, but can be overcome by integrating the roles into a cohesive unit focused on delivering a high-value product. Integrating Program Management with Systems Engineering provides a practical route to better performance for your organization as a whole.

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.

Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox’ Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.

How can we facilitate more effective, efficient, equitable and sustainable solutions to the problems that confound our communities and world? Social marketing guru R. Craig LeFebvre weaves together multi-level theories of change, research and case studies to explain and illustrate the development of social marketing to address some of society’s most vexing problems. The result is a people-centered approach that relies on insight and empathy as much as on data for the inspiration, design and management of programs that strive for changes for good. This text is ideal for students and professionals in health, nonprofit, business, social services, and other areas. “This is it – the comprehensive, brainy road map for tackling wicked social problems. It’s all right here: how to create and innovate, build and implement, manage and measure, scale up and sustain programs that go well beyond influencing individual behaviors, all the way to broad social change in a world that needs the help.”—Bill Novelli, Professor, McDonough School of Business, Georgetown University, former CEO, AARP and founder, Porter Novelli and the Campaign for Tobacco-Free Kids “I’m unaware of a more substantive treatise on social marketing and social change. Theoretically based; pedagogically focused; transdisciplinary; innovative; and action oriented: this book is right for our time, our purpose, and our future thinking and action.”—Robert Gold, MS, PhD, Professor of Public Health and Former Dean of the School of Public Health at the University of Maryland, College Park “This book – like its author – is innovative and forward-looking, yet also well-grounded in the full range of important social marketing fundamentals.”—Edward Maibach, MPH, PhD, University Professor and Director, Center for Climate Change Communication, George Mason University

Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials. It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials. Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis. Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.

Written by a well-known lecturer and consultant to the pharmaceutical industry, this book focuses on the pharmaceutical non-statistician working within a very strict regulatory environment. Statistical Thinking for Clinical Trials in Drug Regulation presents the concepts and statistical thinking behind medical studies with a direct connection to the regulatory environment so that readers can be clear where the statistical methodology fits in with industry requirements. Pharmaceutical-related examples are used throughout to set the information in context. As a result, this book provides a detailed overview of the statistical aspects of the design, conduct, analysis and presentation of data from clinical trials within drug regulation. Statistical Thinking for Clinical Trials in Drug Regulation: Assists pharmaceutical personnel in communicating effectively with statisticians using statistical language Improves the ability to read and understand statistical methodology in papers and reports and to critically appraise that methodology Helps to understand the statistical aspects of the regulatory framework better quoting extensively from regulatory guidelines issued by the EMEA (European Medicines Evaluation Agency), ICH (International Committee on Harmonization and the FDA (Food and Drug Administration)

This is the long-awaited update on the bestselling book that offers a practical, accessible reference manual for faculty in any discipline. This new edition contains up-to-date information on technology as well as expanding on the ideas and strategies presented in the first edition. It includes more than sixty-one chapters designed to improve the teaching of beginning, mid-career, or senior faculty members. The topics cover both traditional tasks of teaching as well as broader concerns, such as diversity and inclusion in the classroom and technology in educational settings.

Praise for Critical Thinking in Clinical Practice, Third Edition «Eileen Gambrill is unparalleled in her ability to describe common flaws and biases in clinical decision making. The result in this revised edition is a steadfast call for change that also acknowledges the demands of practice. A must-read for clinicians and researchers alike.» —Elizabeth K. Anthony, PhD, Assistant Professor, School of Social Work, Arizona State University «This Third Edition builds upon the impressive strengths of Gambrill's prior treatments of the topic to support the notion that critical thinking is a teachable skill and one essential for contemporary practice in the human services. This book should be the default authority on the topic of critical thinking for human service professionals and would be an excellent textbook.» —Bruce A. Thyer, PhD, LCSW, Professor and former Dean, Florida State University College of Social Work «I was skeptical about how Critical Thinking in Clinical Practice could be improved, but Eileen Gambrill has succeeded! Her articulation of critical thinking skills for clinical decisions ultimately will benefit the people we serve.» —Joanne Yaffe, PhD, ACSW, Associate Professor of Social Work and Adjunct Associate Professor of Psychiatry, University of Utah A balanced and illustrative guide to incorporating critical-thinking values, knowledge, and skills into clinical education and practice Now in a third edition, Critical Thinking in Clinical Practice is written for helping professionals who want to think more clearly about the decisions they make and the context in which they make them. It is a practical volume for clinicians who would like to expand their knowledge of common pitfalls and fallacies in clinical reasoning. As in earlier editions, this Third Edition draws on research related to problem solving and decision making, illustrating the relevance of research findings to everyday clinical practice and policy. Revised throughout, the new edition includes discussion of: The influence of pharmaceutical companies on the helping professions, including disease mongering—the creation of bogus risks, problems, and needless worries Different kinds of propaganda in the helping professions that compromise informed consent Additional coverage of classification, pathology, reliance on authority, and hazards in data collection The development of decision aids of value to both professionals and clients The relative contribution of specific interventions compared to nonspecific factors to positive outcome Factors related to decision making in multidisciplinary teams New developments regarding intuitive and analytic reasoning The pragmatic theory of fallacies Designed to enhance the quality of services offered to clients, Critical Thinking in Clinical Practice, Third Edition is filled with insightful examples, useful lists, websites, and guidelines, presenting an essential resource for all helping professionals and students in the helping professions.