Computational Statistics in the Earth Sciences
Cambridge University Press (Verlag)
978-1-107-09600-4 (ISBN)
Based on a course taught by the author, this book combines the theoretical underpinnings of statistics with the practical analysis of Earth sciences data using MATLAB. The book is organized to introduce the underlying concepts, and then extends these to the data, covering methods that are most applicable to Earth sciences. Topics include classical parametric estimation and hypothesis testing, and more advanced least squares-based, nonparametric, and resampling estimators. Multivariate data analysis, not often encountered in introductory texts, is presented later in the book, and compositional data is treated at the end. Datasets and bespoke MATLAB scripts used in the book are available online, as well as additional datasets and suggested questions for use by instructors. Aimed at entering graduate students and practicing researchers in the Earth and ocean sciences, this book is ideal for those who want to learn how to analyse data using MATLAB in a statistically-rigorous manner.
Alan D. Chave is a Senior Scientist at Woods Hole Oceanographic Institution (WHOI), Massachusetts. He has been a Chartered Statistician since 2003, and has taught a graduate-level course in statistics in the MIT/WHOI Joint Program for twenty years. For over forty years, he has conducted research utilizing the magnetotelluric method, primarily in the oceans, and using electromagnetic measurements to define the barotropic water velocity. Dr Chave has also designed instrumentation for optical and chemical measurements in the ocean, and has played a leading role in the development of long-term ocean observatories worldwide. He has been an associate editor of the Journal of Geophysical Research and editor-in-chief of Reviews of Geophysics, and is the co-author of The Magnetotelluric Method (Cambridge, 2012).
Preface; 1. Probability concepts; 2. Statistical concepts; 3. Statistical distributions; 4. Characterization of data; 5. Point, interval and ratio estimators; 6. Hypothesis testing; 7. Nonparametric methods; 8. Resampling methods; 9. Linear regression; 10. Multivariate statistics; 11. Compositional data; Appendix: MATLAB functions to produce ternary diagrams; References; Index.
Erscheinungsdatum | 21.10.2017 |
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Zusatzinfo | 169 Halftones, black and white |
Verlagsort | Cambridge |
Sprache | englisch |
Maße | 191 x 253 mm |
Gewicht | 1180 g |
Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
Mathematik / Informatik ► Mathematik ► Statistik | |
Naturwissenschaften ► Geowissenschaften ► Geologie | |
ISBN-10 | 1-107-09600-6 / 1107096006 |
ISBN-13 | 978-1-107-09600-4 / 9781107096004 |
Zustand | Neuware |
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