Computational Statistics in the Earth Sciences
Autor Alan D Chaveen Limba Engleză Hardback – 19 oct 2017
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Specificații
ISBN-13: 9781107096004
ISBN-10: 1107096006
Pagini: 464
Ilustrații: 169 b/w illus.
Dimensiuni: 189 x 254 x 27 mm
Greutate: 1.17 kg
Editura: Cambridge University Press
Locul publicării:New York, United States
ISBN-10: 1107096006
Pagini: 464
Ilustrații: 169 b/w illus.
Dimensiuni: 189 x 254 x 27 mm
Greutate: 1.17 kg
Editura: Cambridge University Press
Locul publicării:New York, United States
Cuprins
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.
Recenzii
'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
'… this book will be a welcome and invaluable addition to any earth scientist's library.' Sven Treitel, The Leading Edge
Descriere
This book combines theoretical underpinnings of statistics with practical analysis of Earth sciences data using MATLAB. Supplementary resources are available online.