Statistical Methods And The Improvement Of Data Quality


Statistical Methods And The Improvement Of Data Quality
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Statistical Methods And The Improvement Of Data Quality


Statistical Methods And The Improvement Of Data Quality
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Author : Tommy Wright
language : en
Publisher: Academic Press
Release Date : 2014-05-10

Statistical Methods And The Improvement Of Data Quality written by Tommy Wright and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Reference categories.


Statistical Methods and the Improvement of Data Quality contains the proceedings of The Small Conference on the Improvement of the Quality of Data Collected by Data Collection Systems, held on November 11-12, 1982, in Oak Ridge, Tennessee. The conference provided a forum for discussing the use of statistical methods to improve data quality, with emphasis on the problems of data collection systems and how to handle them using state-of-the-art techniques. Comprised of 16 chapters, this volume begins with an overview of some of the limitations of surveys, followed by an annotated bibliography on frames from which the probability sample is selected. The reader is then introduced to sample designs and methods for collecting data over space and time; response effects to behavior and attitude questions; and how to develop and use error profiles. Subsequent chapters focus on principles and methods for handling outliers in data sets; influence functions, outlier detection, and data editing; and application of pattern recognition techniques to data analysis. The use of exploratory data analysis as an aid in modeling and statistical forecasting is also described. This monograph is likely to be of primary benefit to students taking a general course in survey sampling techniques, and to individuals and groups who deal with large data collection systems and are constantly seeking ways to improve the overall quality of their data.



Multivariate Statistical Methods In Quality Management


Multivariate Statistical Methods In Quality Management
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Author : Kai Yang
language : en
Publisher: McGraw Hill Professional
Release Date : 2004-03-17

Multivariate Statistical Methods In Quality Management written by Kai Yang and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-17 with Technology & Engineering categories.


Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods



Statistical Methods For Quality Assurance


Statistical Methods For Quality Assurance
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Author : Stephen B. Vardeman
language : en
Publisher: Springer
Release Date : 2016-08-26

Statistical Methods For Quality Assurance written by Stephen B. Vardeman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-26 with Mathematics categories.


This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings



Statistical Methods For Quality Improvement


Statistical Methods For Quality Improvement
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Author : Thomas P. Ryan
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20

Statistical Methods For Quality Improvement written by Thomas P. Ryan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Technology & Engineering categories.


Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.



Statistical Thinking


Statistical Thinking
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Author : Roger W. Hoerl
language : en
Publisher: John Wiley & Sons
Release Date : 2020-09-16

Statistical Thinking written by Roger W. Hoerl and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-16 with Business & Economics categories.


Apply statistics in business to achieve performance improvement Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research. The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use. Updates to this edition include: A new chapter on data, assessing data pedigree (quality), and acquisition tools Discussion of the relationship between statistical thinking and data science Explanation of the proper role and interpretation of p-values (understanding of the dangers of “p-hacking”) Differentiation between practical and statistical significance Introduction of the emerging discipline of statistical engineering Explanation of the proper role of subject matter theory in order to identify causal relationships A holistic framework for variation that includes outliers, in addition to systematic and random variation Revised chapters based on significant teaching experience Content enhancements based on student input This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.



Quality Improvement Through Statistical Methods


Quality Improvement Through Statistical Methods
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Author : Bovas Abraham
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Quality Improvement Through Statistical Methods written by Bovas Abraham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


This book is based on the papers presented at the International Conference 'Quality Improvement through Statistical Methods' in Cochin, India during December 28-31, 1996. The Conference was hosted by the Cochin University of Science and Technology, Cochin, India; and sponsored by the Institute for Improvement in Quality and Productivity (IIQP) at the University of Waterloo, Canada, the Statistics in Industry Committee of the International Statistical Institute (lSI) and by the Indian Statistical Institute. There has been an increased interest in Quality Improvement (QI) activities in many organizations during the last several years since the airing of the NBC television program, "If Japan can ... why can't we?" Implementation of QI meth ods requires statistical thinking and the utilization of statistical tools, thus there has been a renewed interest in statistical methods applicable to industry and technology. This revitalized enthusiasm has created worldwide discussions on Industrial Statistics Research and QI ideas at several international conferences in recent years. The purpose of this conference was to provide a forum for presenting and ex changing ideas in Statistical Methods and for enhancing the transference of such technologies to quality improvement efforts in various sectors. It also provided an opportunity for interaction between industrial practitioners and academia. It was intended that the exchange of experiences and ideas would foster new international collaborations in research and other technology transfers.



Statistical Methods For Quality Reliability And Maintainability


Statistical Methods For Quality Reliability And Maintainability
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Author : K. MURALIDHARAN
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2012-05-16

Statistical Methods For Quality Reliability And Maintainability written by K. MURALIDHARAN and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-16 with Technology & Engineering categories.


A fine blend of the three disciplines, viz. quality, reliability and maintainability, this book provides a clear understanding of the concepts and discusses their applications using statistical tools and techniques. The concepts are critically assessed and explained to enable their use for management decision-making. The book describes many current topics such as six sigma, capability maturity model integration (CMMI), process data management, reliability system models, repairable system models, maintainability assessment and design and testing concepts. It is intended as a textbook for the undergraduate students of Mechanical Engineering and Production and Industrial Engineering. The book will also be useful to the postgraduate students of Applied Statistics, Quality and Reliability, and Quality and Productivity Management as well as to the management and engineering professionals. KEY FEATURES : Provides charts and plots to explain the concepts discussed. Gives an account of most recent developments. Gives illustrations of practical situations where tools can be applied immediately. Interspersed with plenty of worked-out examples to reinforce the concepts. Includes chapter-end exercises to drill the students in self-study.



Statistical Methods For Quality Assurance


Statistical Methods For Quality Assurance
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Author : Stephen B. Vardeman
language : en
Publisher: Springer
Release Date : 2016-03-03

Statistical Methods For Quality Assurance written by Stephen B. Vardeman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-03 with Mathematics categories.


The rich set of examples and problems integrated throughout this book will help readers gain a better understanding of where and how to apply Statistical Quality Control (SQC) tools. Real projects, cases and data sets show clearly how SQC tools are used in practice. Topics are covered in the right amount of detail to give insight into their relative importance in modern quality assurance and the ability to immediately use them.



Information Quality


Information Quality
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Author : Ron S. Kenett
language : en
Publisher: John Wiley & Sons
Release Date : 2016-10-13

Information Quality written by Ron S. Kenett and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-13 with Mathematics categories.


Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.



Statistical Methods For Hospital Monitoring With R


Statistical Methods For Hospital Monitoring With R
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Author : Anthony Morton
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-27

Statistical Methods For Hospital Monitoring With R written by Anthony Morton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-27 with Medical categories.


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.