Quantitative Methods of Data Analysis for the Physical Sciences and Engineering

Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.

Douglas G. Martinson (Author)

9781107029767, Cambridge University Press

Hardback, published 20 September 2018

626 pages
25.3 x 17.8 x 3.3 cm, 1.38 kg

'This is a competent development of many data analysis methods … Overall, the book is the outgrowth of teaching the subject for 30 years, which shows in the well-developed, clear narrative descriptions accompanying the theory.' D. A. Vaccari, Choice

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.

Part I. Fundamentals: 1. The nature of data and analysis
2. Probability theory
3. Statistics
Part II. Fitting Curves to Data
4. Interpolation
5. Smoothed curve fitting
6. Special curve fitting
Part III. Sequential Data Fundamentals: 7. Serial products
8. Fourier series
9. Fourier transform
10. Fourier sampling theory
11. Spectral analysis
12. Cross spectral analysis
13. Filtering and deconvolution
14. Linear parametric models
15. Empirical orthogonal function (EOF) analysis
A1. Overview of matrix algebra
A2. Uncertainty analysis
References
Index.

Subject Areas: Data capture & analysis [UNC], Computer programming / software development [UM], Maths for engineers [TBJ], Earth sciences [RB], Geophysics [PHVG], Mathematical modelling [PBWH], Data analysis: general [GPH]