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Statistical Models

  • Richard J. Huggett
Part of the Springer Series in Physical Environment book series (SSPENV, volume 1)

Abstract

An outgrowth of the relative frequency view of probability is the development of inductive statistical models. The statistical models used in the Earth sciences are many and varied. They range from simple techniques, such as the chi-square test, Student’s t-test, and the more versatile analysis of variance, all of which are used in testing the significance of differences between class data; through the more sophisticated techniques of regression and correlation, which are used for establishing relationships between variables; to complex multivariate models, such as multivariate regression, multivariate correlation, canonical correlation, multidimensional scaling, and principal component analysis, which enable relationships to be detected within sets of variables.

Keywords

Principal Component Analysis Drainage Basin Canonical Correlation Slope Gradient Principal Coordinate Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1985

Authors and Affiliations

  • Richard J. Huggett
    • 1
  1. 1.School of GeographyUniversity of ManchesterManchesterEngland

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