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Author: Ton de Waal
Publisher: John Wiley & Sons
ISBN: 0470542802
Category : Mathematics
Languages : en
Pages : 464
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Book Description
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.
Author: Ton de Waal
Publisher: John Wiley & Sons
ISBN: 0470542802
Category : Mathematics
Languages : en
Pages : 464
Get Book Here
Book Description
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.
Author: Ton de Waal
Publisher: John Wiley & Sons
ISBN: 0470904836
Category : Mathematics
Languages : en
Pages : 453
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Book Description
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.
Author: Michael G. Pecht
Publisher: John Wiley & Sons
ISBN: 1119515351
Category : Technology & Engineering
Languages : en
Pages : 973
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Book Description
An indispensable guide for engineers and data scientists in design, testing, operation, manufacturing, and maintenance A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to: assess methods for damage estimation of components and systems due to field loading conditions assess the cost and benefits of prognostic implementations develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles and/or timely repair actions; obtain knowledge of load history for future design, qualification, and root cause analysis reduce the occurrence of no fault found (NFF) subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.
Author: Wil M. P. van der Aalst
Publisher: Springer Nature
ISBN: 3030373347
Category : Computers
Languages : en
Pages : 441
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Book Description
This book constitutes the post-conference proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019. The 27 full and 8 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were automatically rejected without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; and analysis of dynamic behavior through event data.
Author: Álvaro Rocha
Publisher: Springer
ISBN: 3030161811
Category : Technology & Engineering
Languages : en
Pages : 997
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Book Description
This book includes a selection of articles from The 2019 World Conference on Information Systems and Technologies (WorldCIST’19), held from April 16 to 19, at La Toja, Spain. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges in modern information systems and technologies research, together with their technological development and applications. The book covers a number of topics, including A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications.
Author: Ger Snijkers
Publisher: John Wiley & Sons
ISBN: 1118447913
Category : Mathematics
Languages : en
Pages : 646
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Book Description
Designing and Conducting Business Surveys provides a coherent overview of the business survey process, from start to finish. It uniquely integrates an understanding of how businesses operate, a total survey error approach to data quality that focuses specifically on business surveys, and sound project management principles. The book brings together what is currently known about planning, designing, and conducting business surveys, with producing and disseminating statistics or other research results from the collected data. This knowledge draws upon a variety of disciplines such as survey methodology, organizational sciences, sociology, psychology, and statistical methods. The contents of the book formulate a comprehensive guide to scholarly material previously dispersed among books, journal articles, and conference papers. This book provides guidelines that will help the reader make educated trade-off decisions that minimize survey errors, costs, and response burden, while being attentive to survey data quality. Major topics include: • Determining the survey content, considering user needs, the business context, and total survey quality • Planning the survey as a project • Sampling frames, procedures, and methods • Questionnaire design and testing for self-administered paper, web, and mixed-mode surveys • Survey communication design to obtain responses and facilitate the business response process • Conducting and managing the survey using paradata and project management tools • Data processing, including capture, editing, and imputation, and dissemination of statistical outputs Designing and Conducting Business Surveys is an indispensable resource for anyone involved in designing and/or conducting business or organizational surveys at statistical institutes, central banks, survey organizations, etc.; producing statistics or other research results from business surveys at universities, research organizations, etc.; or using data produced from business surveys. The book also lays a foundation for new areas of research in business surveys.
Author: Paul P. Biemer
Publisher: John Wiley & Sons
ISBN: 1119041694
Category : Social Science
Languages : en
Pages : 801
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Book Description
Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data sets This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error. This book: • Features various error sources, and the complex relationships between them, in 25 high-quality chapters on the most up-to-date research in the field of TSE • Provides comprehensive reviews of the literature on error sources as well as data collection approaches and estimation methods to reduce their effects • Presents examples of recent international events that demonstrate the effects of data error, the importance of survey data quality, and the real-world issues that arise from these errors • Spans the four pillars of the total survey error paradigm (design, data collection, evaluation and analysis) to address key data quality issues in official statistics and survey research Total Survey Error in Practice is a reference for survey researchers and data scientists in research areas that include social science, public opinion, public policy, and business. It can also be used as a textbook or supplementary material for a graduate-level course in survey research methods.
Author: Vera Toepoel
Publisher: SAGE
ISBN: 1473947693
Category : Social Science
Languages : en
Pages : 281
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Book Description
Vera Toepoel’s practical, how-to guide to doing surveys online takes you through the entire process of using surveys, from systematically recruiting respondents, to designing the internet survey, to processing the survey data and writing it up. This book helps students and researchers in identifying possible strategies to make the best use of online surveys, providing pro’s and con’s, and do’s and don’ts for each strategy. It also explores the latest opportunities and developments that have arisen in the field of online surveys, including using social networks, and provides expert guidance and examples of best practice throughout. Suitable for those starting a research project or conducting a survey in a professional capacity, this book is the ideal go-to reference for anyone using internet surveys, be it a beginner or a more experienced survey researcher.
Author: Anton Eremeev
Publisher: Springer
ISBN: 3319938002
Category : Computers
Languages : en
Pages : 351
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Book Description
This book constitutes extended, revised and selected papers from the 7th International Conference on Optimization Problems and Their Applications, OPTA 2018, held in Omsk, Russia in July 2018. The 27 papers presented in this volume were carefully reviewed and selected from a total of 73 submissions. The papers are listed in thematic sections, namely location problems, scheduling and routing problems, optimization problems in data analysis, mathematical programming, game theory and economical applications, applied optimization problems and metaheuristics.
Author: Dr. Md. Uzir Hossain Uzir
Publisher: Partridge Publishing Singapore
ISBN: 1543764762
Category : Technology & Engineering
Languages : en
Pages : 241
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Book Description
A brand is a valuable asset, and loyalty to a particular brand is the source of revenue and profitability of the business. Brand loyalty is significant for the business growth and expansion of companies in the electronics sector. A populated country, Bangladesh has a substantial expenditure on electronic appliances, and the demand for these household items increases over the period; however, customers are not always loyal to a particular brand. Marketing literature shows that customer satisfaction and brand confidence directly affect brand loyalty, and brand trust mediates their relationship. Due to the technological advance of social media, technology has an essential role in the customer's decision to buy household appliances. The existing literature has not focused on this massive demand for electronic appliances, customer satisfaction, loyalty, trust, and social media's significant role in consumer buying behavior. The book shoed the investigation of the effect of customer satisfaction and brand trust of electronic home appliances on brand loyalty and the mediating role of brand trust in customer satisfaction and trust relationship. The study also examined the extent to which customers believe social media information influences them. The study gathered data from 523 Bangladeshi respondents from Dhaka by conducting a survey. The data were analyzed with SPSS and CB-SEM (AMOS) for the hypothesis test. The findings revealed that customer satisfaction and brand trust significantly impact brand loyalty, and social media moderates those significant relationships. The result of the study contributed to the expectancy-disconfirmation theory, trust-commitment theory, brand loyalty theory, and theory of reasoned action by presenting empirically-based insight into customer satisfaction, brand trust, and brand loyalty constructs in electronic home appliances in Bangladesh. In addition, the results provided a practical insight into marketing and brand management. They suggested the practicing managers in developing product quality with customer preference, building trust through maintaining brand image and creating awareness among the customers, and considering the significance of social media and its usage. The research used probabilistic sampling techniques, both rural and urban customers, only a single home appliance, and PLS-SEM statistical tool for analysis. Future researchers could focus and include other variables such as price or advertising; consider loyalty separately, and use both urban and rural customers to have better predictions.
