National Science Library of Georgia

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

By: Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2018Description: 1 online resource (xiv, 614 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781139342568 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 519.5 23
LOC classification:
  • QA276 .M3375 2018
Online resources:
Contents:
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.
Summary: This book provides 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. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes.
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Title from publisher's bibliographic system (viewed on 24 Sep 2018).

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.

This book provides 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. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes.

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