Download or read book Data Uncertainty and Important Measures written by Christophe Simon and published by John Wiley & Sons. This book was released on 2018-03-13 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The application to system reliability assessment illustrates the concept. In the second part, evidential networks as a new tool to model uncertainty in reliability and risk analysis is proposed and described. Then it is applied on SIS performance assessment and in risk analysis of a heat sink. In the third part, Bayesian and evidential networks are used to deal with important measures evaluation in the context of uncertainties.
Download or read book How to Measure Anything written by Douglas W. Hubbard and published by Wiley. This book was released on 2010-03-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now updated with new research and even more intuitive explanations, a demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions This insightful and eloquent book will show you how to measure those things in your own business that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI. Adds even more intuitive explanations of powerful measurement methods and shows how they can be applied to areas such as risk management and customer satisfaction Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas Offers practical methods for measuring a variety of "intangibles" Adds recent research, especially in regards to methods that seem like measurement, but are in fact a kind of "placebo effect" for management – and explains how to tell effective methods from management mythology Written by recognized expert Douglas Hubbard-creator of Applied Information Economics-How to Measure Anything, Second Edition illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.
Download or read book Data Science written by Carlos Alberto De Bragança Pereira and published by MDPI. This book was released on 2021-09-02 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science has emerged as a multidisciplinary field to support data-driven activities, integrating and developing ideas, methods, and processes to extract information from data. This includes methods built from different knowledge areas: Statistics, Computer Science, Mathematics, Physics, Information Science, and Engineering. This mixture of areas has given rise to what we call Data Science. New solutions to the new problems are reproducing rapidly to generate large volumes of data. Current and future challenges require greater care in creating new solutions that satisfy the rationality for each type of problem. Labels such as Big Data, Data Science, Machine Learning, Statistical Learning, and Artificial Intelligence are demanding more sophistication in the foundations and how they are being applied. This point highlights the importance of building the foundations of Data Science. This book is dedicated to solutions and discussions of measuring uncertainties in data analysis problems.
Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-05-02 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.
Download or read book Uncertainty propagation and importance measure assessment written by Enrico Zio and published by FonCSI. This book was released on 2013-12-14 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors investigate the effects that different representations of epistemic uncertainty have on practical risk assessment problems. Two different application problems are considered: 1. the estimation of component importance measures in the presence of epistemic uncertainties; 2. the propagation of uncertainties through a risk flooding model. The focus is on the epistemic uncertainty affecting the parameters of the models that describe the components’ failures due to incomplete knowledge of their values. This epistemic uncertainty is represented using probability distributions when sufficient data is available for statistical analysis, and by possibility distributions when the information available to define the parameters’ values comes from experts, in the form of imprecise quantitative statements or judgments. Three case studies of increasing complexity are presented: a pedagogical example of importance measure assessment on a three-component system from the literature; assessment of importance measures for the auxiliary feed water system of a nuclear pressurized water reactor; an application in environmental modelling, with an analysis of uncertainty propagation in a hydraulic model for the risk-based design of a flood protection dike.
Download or read book Measurements and their Uncertainties written by Ifan Hughes and published by OUP Oxford. This book was released on 2010-07-02 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.
Download or read book Dealing with Uncertainties written by Manfred Drosg and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with Uncertainties proposes and explains a new approach for the analysis of uncertainties. Firstly, it is shown that uncertainties are the consequence of modern science rather than of measurements. Secondly, it stresses the importance of the deductive approach to uncertainties. This perspective has the potential of dealing with the uncertainty of a single data point and of data of a set having differing weights. Both cases cannot be dealt with the inductive approach, which is usually taken. This innovative monograph also fully covers both uncorrelated and correlated uncertainties. The weakness of using statistical weights in regression analysis is discussed. Abundant examples are given for correlation in and between data sets and for the feedback of uncertainties on experiment design.
Download or read book Data Science Measuring Uncertainties written by Carlos Alberto De Bragança Pereira and published by . This book was released on 2021 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science has emerged as a multidisciplinary field to support data-driven activities, integrating and developing ideas, methods, and processes to extract information from data. This includes methods built from different knowledge areas: Statistics, Computer Science, Mathematics, Physics, Information Science, and Engineering. This mixture of areas has given rise to what we call Data Science. New solutions to the new problems are reproducing rapidly to generate large volumes of data. Current and future challenges require greater care in creating new solutions that satisfy the rationality for each type of problem. Labels such as Big Data, Data Science, Machine Learning, Statistical Learning, and Artificial Intelligence are demanding more sophistication in the foundations and how they are being applied. This point highlights the importance of building the foundations of Data Science. This book is dedicated to solutions and discussions of measuring uncertainties in data analysis problems.
Download or read book An Introduction to Uncertainty in Measurement written by L. Kirkup and published by Cambridge University Press. This book was released on 2006-06-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.
Download or read book Data and Error Analysis written by William Lichten and published by Addison-Wesley. This book was released on 1999 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the lab/experimentation course in physics depts. and/or any course in physics, chemistry, geology, etc. with a lab component focusing on data and error analysis. Designed to help science students process data without lengthy and boring computations, this text/disk package provides useful algorithms and programs that allow students to do analysis more quickly than was previously possible. Using a "learn by doing" approach, it provides simple, handy rules for handling data and estimating errors both by graphical and analytic methods without long discussions and involved theoretical derivations.
Download or read book Measurement Uncertainty in Chemical Analysis written by Paul De Bièvre and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.
Download or read book Evaluating the Measurement Uncertainty written by I Lira and published by CRC Press. This book was released on 2002-04-09 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is now widely recognized that measurement data should be properly analyzed to include an assessment of their associated uncertainty. Since this parameter allows for a meaningful comparison of the measurement results and for an evaluation of their reliability, its expression is important not only in the specialized field of scientific metrology, but also in industry, trade, and commerce. General rules for evaluating and expressing the uncertainty are given in the internationally accepted ISO Guide to the Expression of Uncertainty in Measurement, generally known as the GUM. Evaluating the Measurement Uncertainty details the theoretical framework on which the GUM is based and provides additional material on more advanced topics such as least-squares adjustment and Bayesian statistics. The book does not require previous knowledge other than elementary calculus and can be read as a complement to the GUM or as a stand-alone reference source. It stresses fundamental principles and illustrates their applications through numerous examples taken from many different fields of metrology. The book includes practical guidance as well as theoretical aspects, resulting in an invaluable resource for metrologists, engineers, physicists, and graduate students involved with measurements in academia and industry.
Download or read book The Uncertainty of Measurements written by Shri Krishna Kimothi and published by Quality Press. This book was released on 2001-11-01 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: The uncertainty of measurement results is drawing attention of managers, metrologists and customers. The accuracy of measurements affects all of us in trade, commerce, safety, health care environmental protection and more. The quality of these measurements are regulated by a variety of government agencies. Measurement also plays an important role in manufacturing and service organizations. Use this book to learn more about metrology and the need for reliable measurements. You can also learn about measurement system and quality of measurement systems, objectives and methods. Statistical techniques in metrology are also explained. Examples of measurement data and random variables, probability density functions, sampling distribution, statistical estimation degrees of freedom and regression are included. An entire chapter is devoted to measurement errors. The book goes in-depth into explaining national and international measurement systems and standards, and includes a complete chapter on calibration and measurement trace ability. Measurement Uncertainty will show how to evaluate various uncertainties in measurements using several approaches including international consensus. Calibration laboratories can look specifically at the chapter on that profession to guide them in their measurement improvements. Kimothi also looks at specific industries and their measurement capabilities and includes examples of R&R studies. A great resource for the CQE, CQT, CCT, CSSBB certification exams!
Download or read book Measurements for Decision Making written by Giulio Barbato and published by Società Editrice Esculapio. This book was released on 2013 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the technical-scientific field, many decisions are supported by measurements. However, it is essential to assign to measurement results their actual meaning to achieve a correct decision. This aspect is particularly important and formally required when operating in Quality Systems. Therefore, measures management must be rigorous and it can find a concrete support in the topics discussed in this volume, because of the attention to metrological part and the removal of unnecessary restrictions.
Download or read book Introduction to Error Analysis written by Jack Merrin and published by Createspace Independent Publishing Platform. This book was released on 2017-08-29 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Great scientists master the math behind the science. Do you still delay mastering data analysis, keeping you from more accurate, rigorous, and higher certainty conclusions? Jack Merrin, Ph.D. Princeton University, is a physicist who has helped hundreds of students with math and physics, taught physics labs, and used error analysis through 25 years of research. You can surely learn the right statistical methods from Jack. Introduction to Error Analysis is more than a collection of ad-hoc statistical theory. It is an easy-to-read blueprint used by scientists for presenting correct results. Transform your experimental perspective to confidence. Learn reusable principles for each new scientific project. This book covers reporting measurements and uncertainties, propagation of error, combining results, curve fitting, essential statistical concepts, and much, much, more. You might love this book if: You are doing lab reports or actual research, and it's time to get serious about data analysis. You want to focus on the essential calculations, not on time-wasting theory. You want adaptable MATLAB code for each different calculation. Hey, no need to reinvent the wheel. You want to reach correct and unique results using the established convention. You want to know what is correct to spot bad scientific literature. Introduction to Error Analysis is the concise book you need to start building your successful scientific career. If you like easy-to-follow lessons, practical examples, insightful tips, and an author who actually cares about you getting it right, then you'll love Jack's book. Buy Introduction to Error Analysis to start refining your data analysis skills today!
Download or read book Precision Measurement and Fundamental Constants Proceedings written by United States. National Bureau of Standards and published by . This book was released on 1971 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Future Communication Systems Using Artificial Intelligence Internet of Things and Data Science written by Inam Ullah and published by CRC Press. This book was released on 2024-06-14 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems. The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‐centric society of the future. New applications are increasingly reliant on machine‐to‐machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‐optimization for the task at hand while ensuring high dependability and ultra‐low latency. Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‐making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required. AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‐agent systems and network ultra‐broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.
