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

By: Martinson, Douglas G, 1953- author [author.].
Material type: materialTypeLabelBookPublisher: Cambridge ; New York, NY : Cambridge University Press, 2018Copyright date: ©2018Description: xiv, 614 pages : illustrations ; 26 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781107029767; 1107029767.Subject(s): Statistics | Physical sciences -- Statistical methods | Engineering -- Statistical methodsDDC classification: 519.5 Summary: "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 understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible"-- Provided by publisher.
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Item type Current location Call number Status Date due Barcode Item holds
Books Books Main Library: Circulation Section
QA 276 .M37 2018 (Browse shelf) Available 20-033776
Total holds: 0

Includes bibliographical references (pages [596]-598) and index.

"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 understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible"-- Provided by publisher.

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