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Testing for transformations

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

Abstract

In Section 1.8 we outlined briefly the point that difficulties can arise from using multiple regression analysis due to the failure of assumptions made in the ordinary least squares (OLS) analysis. The assumptions can fail because of lack of normality, homoscedasticity, independence, or because the underlying model is not linear in the unknown parameters. In this chapter we examine the use of transformations, either of the response variable or of the explanatory variables, to attempt to satisfy the assumptions of an OLS analysis.

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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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