Computational Statistics in the Earth Sciences (inbunden)
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Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
464
Utgivningsdatum
2017-10-19
Förlag
Cambridge University Press
Illustrationer
169 b/w illus.
Dimensioner
259 x 196 x 26 mm
Vikt
1189 g
Antal komponenter
1
ISBN
9781107096004

Computational Statistics in the Earth Sciences

With Applications in MATLAB

av Alan D Chave
Inbunden,  Engelska, 2017-10-19
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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.
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Fler böcker av Alan D Chave

  • The Magnetotelluric Method

    The Magnetotelluric Method

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    The magnetotelluric method is a technique for imaging the electrical conductivity and structure of the Earth, from the near surface down to the 410 km transition zone and beyond. This book forms the first comprehensive overview of magnetotellurics...

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  • Magnetotelluric Method

    Magnetotelluric Method

    Alan D Chave, Alan G Jones

    The magnetotelluric method is a technique for imaging the electrical conductivity and structure of the Earth, from the near surface down to the 410 km transition zone and beyond. This book forms the first comprehensive overview of magnetotellurics...

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Recensioner i media

'One of the main strengths of this book is the combination of mathematical rigor with extensive examples, allowing readers to work through case studies to better understand the concepts presented. The tool used for this purpose is MATLAB, which is widely used in the earth science community. Examples are drawn from geophysics, astrophysics, and anthropology (among others). Both the scripts and the data examples used in the book are available for download from the publisher's website. ... This book is an ideal guide for graduate students seeking a comprehensive and rigorous understanding of statistical methods in earth sciences. For the more mature earth scientist (and I include myself in that number), it provides a useful reference to widely used statistical concepts that many of us regularly encounter.' Lucy MacGregor, The Leading Edge

'... this book will be a welcome and invaluable addition to any earth scientist's library.' Sven Treitel, The Leading Edge

Övrig information

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).

Innehållsförteckning

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.

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