Chapter 16. Regression Analysis (RA)

  1. Clemens Reimann M.Sc. in Mineralogy and Petrology, Ph.D. in Geosciences, D.Sc. in Applied Geochemistry lecturer senior geochemist director professor chairman acting vice president associate editor1,
  2. Peter Filzmoser Applied Mathematics visiting professor2,
  3. Robert G. Garrett Mining Geology and Applied Geochemistry Emeritus Scientist3,
  4. Rudolf Dutter M.Sc., Ph.D. senior statistician full professor post-doctoral fellow2

Published Online: 18 APR 2008

DOI: 10.1002/9780470987605.ch16

Book Title

Statistical Data Analysis Explained: Applied Environmental Statistics with R

Statistical Data Analysis Explained: Applied Environmental Statistics with R

Additional Information

How to Cite

Reimann, C., Filzmoser, P., Garrett, R. G. and Dutter, R. (2008) Regression Analysis (RA), in Statistical Data Analysis Explained: Applied Environmental Statistics with R, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470987605.ch16

Author Information

  1. 1

    Geological Survey of Norway, Norway

  2. 2

    Vienna University of Technology, Austria

  3. 3

    Geological Survey of Canada, Canada

Publication History

  1. Published Online: 18 APR 2008
  2. Published Print: 4 APR 2008

ISBN Information

Print ISBN: 9780470985816

Online ISBN: 9780470987605

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CHAPTER TOOLS

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Keywords:

  • regression analysis (RA) and regression equations;
  • regression analysis data requirement;
  • response and explanatory variables;
  • classical least squares (LS) regression;
  • multiple regression;
  • LS residuals and Tukey-based EDA symbology;
  • robust regression;
  • regression diagnostics and QQ-plot

Summary

This chapter contains sections titled:

  • Data requirements for regression analysis

  • Multiple regression

  • Classical least squares (LS) regression

  • Robust regression

  • Model selection in regression analysis

  • Other regression methods

  • Summary

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