Quantitative methods of data analysis for the physical sciences and engineering / Douglas G. Martinson (Columbia University, New York)

Englisch

Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2018

1 Online-Ressource (1 online resource)

Title from publisher's bibliographic system (viewed on 24 Sep 2018)

Erscheint auch als: Druck-Ausgabe- Martinson, Douglas G. *1953-*: Quantitative methods of data analysis for the physical sciences and engineering. - Cambridge : Cambridge University Press, 2018. - xiv, 614 Seiten

978-1-139-34256-8 : ebook

1-139-34256-8

Weitere Ausgaben: 978-1-107-02976-7 (Druckausgabe) : print

DOI: 10.1017/9781139342568

*978-1-107-02976-7 - ISBN *1-107-02976-7

*Ingenieurwissenschaften / Datenanalyse / Harmonische Analyse / Statistik

*Statistics ; Physical sciences -- Statistical methods ; Engineering -- Statistical methods

*Engineering ; Physical sciences ; Statistics ; Physical sciences ; Statistical methods ; Engineering ; Statistical methods

Klassifikation der Library of Congress: QA276

Dewey Dezimal-Klassifikation: 519.5

Regensburger Verbund-Klassifikation: AK 30100: A Allgemeines / AK 10000-AK 53900 Wissenschaftskunde und Wissenschaftsorganisation / Wissenschaftsstatistik

Mathematics Subject Classification: *62-01

Mathematics Subject Classification: 62P12

Mathematics Subject Classification: 62P35

Mathematics Subject Classification: 97K80

Mathematics Subject Classification: 62-07

Mathematics Subject Classification: 00A06

"This book provides a thorough and comprehensive coverage of most of the new and important quantitative methods of data analysis for graduate students and practitioners. In recent years, data analysis methods have exploded alongside advanced computing power, and it is critical to understand such methods to get the most out of data, and to extract signal from noise. The book excels in explaining difficult concepts through simple explanations and detailed explanatory illustrations. Most unique is the focus on confidence limits for power spectra and their proper interpretation, something rare or completely missing in other books. Likewise, there is a thorough discussion of how to assess uncertainty via use of Expectancy, and the easy to apply and undsyserstand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible"--

The nature of data and analysis -- Probability theory -- Statistics -- Interpolation -- Smoothed curve fitting -- Special curve fitting -- Serial products -- Fourier series -- Fourier transform -- Fourier sampling theory -- Spectral analysis -- Cross spectral analysis -- Filtering and deconvolution -- Linear parametric modeling -- Empirical orthogonal function (Eof) analysis

https://zbmath.org/?q=an:1401.62002 [Zentralblatt MATH]

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