Statistics of Earth Science Data

Graham J. Borradaile

ISBN 10: 364207815X / ISBN 13: 9783642078156

Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Dez 2010, 2010

About this Item

Neuware -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.

Seller Inventory # 9783642078156

Bibliographic Details

• Title: Statistics of Earth Science Data
• Publisher: Springer Berlin Heidelberg, Springer Berlin Heidelberg Dez 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 364207815X
• ISBN 13: 9783642078156
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 270W x 193H x 21D millimeters 270 millimeters width by 193 millimeters height by 21 millimeters depth
• Weight: 831 grams

About this title

Synopsis

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.