Douglas G. MartinsonCambridge University Press, 9/20/2018EAN 9781107029767, ISBN10: 1107029767Hardcover, 626 pages, 25.3 x 17.8 x 3.3 cmLanguage: EnglishThis 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.Part I. Fundamentals1. The nature of data and analysis2. Probability theory3. StatisticsPart II. Fitting Curves to Data4. Interpolation5. Smoothed curve fitting6. Special curve fittingPart III. Sequential Data Fundamentals7. Serial products8. Fourier series9. Fourier transform10. Fourier sampling theory11. Spectral analysis12. Cross spectral analysis13. Filtering and deconvolution14. Linear parametric models15. Empirical orthogonal function (EOF) analysisA1. Overview of matrix algebraA2. Uncertainty analysisReferencesIndex.
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