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2003, XXVII, 351 p. Printed book Hardcover ▶ 94,95 € | £85.50 | $129.00 ▶ *101,60 € (D) | 104,45 € (A) | CHF 136.50 eBook Available from your library or ▶ springer.com/shop MyCopy Printed eBook for just ▶ € | $ 24.99 ▶ springer.com/mycopy Order online at springer.com ▶ or for the Americas call (toll free) 1-800-SPRINGER ▶ or email us at: [email protected]. ▶ For outside the Americas call +49 (0) 6221-345-4301 ▶ or email us at: [email protected]. The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All prices exclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted. G.J. Borradaile Statistics of Earth Science Data Their Distribution in Time, Space and Orientation ▶ Pre-requisite knowledge of statistics not necessary ▶ Specialist terminology reduced to a minimum ▶ Very graphical approach with many examples The Goals of Data Collection and Its Statistical Treatment in the Earth Sciences The earth sciences are characterised by loose and complex relationships between variables, and the necessity to understand the geographical dis tribution of observations as well as their frequency distribution. Our fre quency distributions and the looseness of relationships reflect the com plexity and intrinsic natural variation in nature, more than measurement error. Furthermore, earth scientists cannot design experiments according to statistical recommendation because the availability and complexity of data are beyond our control. Usually, the system we are studying cannot be isolated into discrete independent variables. These factors influence the first steps of research, how and where to collect specimens or observations. Some issues are particularly troublesome and common in earth science, but are rarely handled in an undergraduate statistics course. These include spatial-sampling methods, orientation data, regionalised variables, time se- ries, identification of cyclicity and pattern, discrimination, multivariate systems, lurking variables and constant-sum data. It is remarkable that most earth-science students confront these issues without formal training or focused consideration.

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2003, XXVII, 351 p.

Printed book

Hardcover▶ 94,95 € | £85.50 | $129.00▶ *101,60 € (D) | 104,45 € (A) | CHF 136.50

eBook

Available from your library or▶ springer.com/shop

MyCopy

Printed eBook for just▶ € | $ 24.99▶ springer.com/mycopy

Order online at springer.com ▶ or for the Americas call (toll free) 1-800-SPRINGER ▶ or email us at:[email protected]. ▶ For outside the Americas call +49 (0) 6221-345-4301 ▶ or email us at:[email protected].

The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% forGermany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All pricesexclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted.

G.J. Borradaile

Statistics of Earth Science DataTheir Distribution in Time, Space and Orientation

▶ Pre-requisite knowledge of statistics not necessary▶ Specialist terminology reduced to a minimum▶ Very graphical approach with many examples

The Goals of Data Collection and Its Statistical Treatment in the Earth Sciences The earthsciences are characterised by loose and complex relationships between variables, andthe necessity to understand the geographical dis tribution of observations as well as theirfrequency distribution. Our fre quency distributions and the looseness of relationshipsreflect the com plexity and intrinsic natural variation in nature, more than measurementerror. Furthermore, earth scientists cannot design experiments according to statisticalrecommendation because the availability and complexity of data are beyond our control.Usually, the system we are studying cannot be isolated into discrete independentvariables. These factors influence the first steps of research, how and where to collectspecimens or observations. Some issues are particularly troublesome and commonin earth science, but are rarely handled in an undergraduate statistics course. Theseinclude spatial-sampling methods, orientation data, regionalised variables, time se-ries, identification of cyclicity and pattern, discrimination, multivariate systems, lurkingvariables and constant-sum data. It is remarkable that most earth-science studentsconfront these issues without formal training or focused consideration.

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http://www.springer.com/978-3-540-43603-4

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