| 书目名称 | Data Modeling for Metrology and Testing in Measurement Science | | 编辑 | Franco Pavese,Alistair B. Forbes | | 视频video | | | 概述 | Takes the reader beyond mainstream methods described in standard texts on data and uncertainty analysis.Real-world applications in a variety of fields, including chemistry, software engineering, and m | | 丛书名称 | Modeling and Simulation in Science, Engineering and Technology | | 图书封面 |  | | 描述 | The aim of this book is to provide, ?rstly, an introduction to probability and statistics especially directed to the metrology and testing ?elds and secondly, a comprehensive, newer set of modelling methods for data and uncertainty analysis that are generally not considered yet within mainstream methods. The book brings, for the ?rst time, a coherent account of these newer me- ods and their computational implementation. They are potentially important because they address problems in application ?elds where the usual hypot- ses that are at the basis of most of the traditional statistical and probabilistic methods, for example, relating to normality of the probability distributions, are frequently not ful?lled to such an extent that an accurate treatment of the calibration or test data using standard approaches is not possible. Additi- ally, the methods can represent alternative ways of data analysis, allowing a deeper understanding of complex situations in measurement. The book lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass modern approaches to ca | | 出版日期 | Book 2009 | | 关键词 | Internet; Mathematica; STATISTICA; Wavelet; calculus; data analysis; fuzzy; metrology; modeling; probability; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-8176-4804-6 | | isbn_ebook | 978-0-8176-4804-6Series ISSN 2164-3679 Series E-ISSN 2164-3725 | | issn_series | 2164-3679 | | copyright | Birkhäuser Boston 2009 |
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发表于 2025-3-21 16:57:44
