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A review of multiple regression by least squares

  • G. Barrie Wetherill
  • P. Duncombe
  • M. Kenward
  • J. Köllerström
  • S. R. Paul
  • B. J. Vowden
Chapter
Part of the Monographs on Statistics and Applied Probability book series (MSAP)

Abstract

For many years multiple regression analysis has been one of the most heavily-used techniques in statistics, and there are applications of it in many different areas. For example, there are applications to control charts (Mandel, 1969), calibration (Mendenhall and Ott, 1971), biology and medicine (Armitage, 1971), survey analysis (Holt et al., 1980) and to time series data (Coen et al., 1969). Unfortunately, the technique is often abused and two factors contribute to this:
  1. (1)

    The basic mathematics is simple, leading to the idea that all that is necessary to use multiple regression is to program some standard formulae.

     
  2. (2)

    There are many computer programs enabling the unwary to proceed with the regression analysis calculations, whether or not the analysis fits.

     

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Copyright information

© G. Barrie Wetherill 1986

Authors and Affiliations

  • G. Barrie Wetherill
    • 1
  • P. Duncombe
    • 2
  • M. Kenward
    • 3
  • J. Köllerström
    • 3
  • S. R. Paul
    • 4
  • B. J. Vowden
    • 3
  1. 1.Department of StatisticsThe University of Newcastle upon TyneUK
  2. 2.Applied Statistics Research UnitUniversity of Kent at CanterburyUK
  3. 3.Mathematical InstituteUniversity of Kent at CanterburyUK
  4. 4.Department of Mathematics and StatisticsUniversity of WindsorCanada

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