[PDF] Analysis Quality And Display Of Official Statistics eBook

Author : Wuyi Zeng
Publisher : Springer Nature
Page : 225 pages
File Size : 19,98 MB
Release : 2022-01-01
Category : Law
ISBN : 9813366028

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This book focuses on how to improve the quality management of official statistics in China. Official statistics help to build an overview of China’s social and economic development and play an important role in policymaking for government as well as in decision-making for enterprises. Because of the great value in reference, the quality of official statistics also constitutes the concern from the public. This book summarizes three levels for understanding the concept of the quality of official statistics and analyzes possible affections from social and economic environment, political and management perspectives. Government statistical data is an important information reflecting China’s economic and social development, an important tool for Party committees at all levels, governments, enterprises and the public to understand and grasp China’s economic operation and social development, an important basis for Party committees and governments at all levels to conduct economic and social management and decision-making and an important reference for enterprises and the public to make decisions on production, operation, investment and consumption. Therefore, the government, enterprises and the public at all levels are demanding more and more government statistics. Accordingly, the quality of government statistical data is becoming more and more important, because it concerns the objectivity and accuracy of government statistical data, the scientificity of economic and social management, the decision-making of Party committees, the correctness of production, operation, investment and consumption decisions of enterprises and the public. Therefore, the quality of government statistical data is extremely important, which is not only the focus of social concern, but also the core issue of government statistics.

Author : Manuel Stagars
Publisher : Springer
Page : 217 pages
File Size : 42,31 MB
Release : 2016-06-16
Category : Business & Economics
ISBN : 1137600632

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This book explores the reliability of official statistical data in the ASEAN (the Association of Southeast Asian Nations), and the benefits of a better vocabulary to discuss the quality of publicly available data to address the needs of all users. It introduces a rigorous method to disaggregate and rate data quality into principal factors containing a total of ten dimensions, which serves as the basis for a discussion on the opportunities and challenges for data quality, capacity building programs and data policy in Southeast Asia. Tools to standardize and monitor statistical capacity and data quality are presented, as well as methods and data sources to analyse data quality. The book analyses data quality in Indonesia, Malaysia, Singapore, the Philippines, Thailand, Vietnam, Brunei, Laos, Cambodia, and Myanmar, before concluding with thoughts on Open Data and the ASEAN Economic Community (AEC).

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
Page : 151 pages
File Size : 30,83 MB
Release : 2017-04-21
Category : Social Science
ISBN : 030945428X

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Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
Page : 195 pages
File Size : 13,71 MB
Release : 2018-01-27
Category : Social Science
ISBN : 0309465370

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The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

Author : Craig A. Hill
Publisher : John Wiley & Sons
Page : 784 pages
File Size : 17,97 MB
Release : 2020-09-29
Category : Social Science
ISBN : 1118976320

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Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.

Author : Alessandro Martinisi
Publisher : Anthem Press
Page : 243 pages
File Size : 42,85 MB
Release : 2020-10-29
Category : Social Science
ISBN : 1785275356

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This book looks at how numbers and statistics have been used to underpin quality in news reporting. In doing so, the aim is to challenge some common assumptions about how journalists engage and use statistics in their quest for quality news. It seeks to improve our understanding about the usage of data and statistics as a primary means for the construction of social reality. This is a task, in our view, that is urgent in times of ‘post-truth’ politics and the rise of ‘fake news’. In this sense, the quest to produce ‘quality’ news, which seems to require incorporating statistics and engaging with data, as laudable and straightforward as it sounds, is instead far more problematic and complex than what is often accounted for.

Author : Ron S. Kenett
Publisher : John Wiley & Sons
Page : 381 pages
File Size : 29,37 MB
Release : 2016-12-19
Category : Mathematics
ISBN : 1118874447

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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.

Author : Stephen B. Vardeman
Publisher : Springer
Page : 447 pages
File Size : 49,53 MB
Release : 2016-08-26
Category : Mathematics
ISBN : 038779106X

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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