Advertisement

Statistics of Earth Science Data

Their Distribution in Time, Space, and Orientation

  • Graham Borradaile
Textbook

Table of contents

  1. Front Matter
    Pages I-XXVII
  2. Graham Borradaile
    Pages 1-33
  3. Graham Borradaile
    Pages 35-59
  4. Graham Borradaile
    Pages 111-131
  5. Graham Borradaile
    Pages 133-156
  6. Graham Borradaile
    Pages 157-185
  7. Graham Borradaile
    Pages 187-220
  8. Graham Borradaile
    Pages 221-245
  9. Graham Borradaile
    Pages 247-292
  10. Graham Borradaile
    Pages 293-326
  11. Graham Borradaile
    Pages 327-336
  12. Graham Borradaile
    Pages 337-343
  13. Back Matter
    Pages 345-353

About this book

Introduction

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.

Keywords

GPS Geoinformationssysteme Geostatistics Normal distribution Probenahme Regression Sampling Spatial data Time series geoscience räumliche Daten

Authors and affiliations

  • Graham Borradaile
    • 1
  1. 1.Geology DepartmentLakehead UniversityThunder BayCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-05223-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07815-6
  • Online ISBN 978-3-662-05223-5
  • Buy this book on publisher's site
Industry Sectors
Pharma
Automotive
Biotechnology
Electronics
IT & Software
Telecommunications
Aerospace
Oil, Gas & Geosciences
Engineering