, Volume 21, Issue 3, pp 219–228 | Cite as

The relation between information and variance analyses

  • W. R. Garner
  • William J. McGill


Analysis of variance and uncertainty analysis are analogous techniques for partitioning variability. In both analyses negative interaction terms due to negative covariance terms that appear when non-orthogonal predictor variables are allowed may occur. Uncertainties can be estimated directly from variances if the form of distribution is assumed. The decision as to which of the techniques to use depends partly on the properties of the criterion variable. Only uncertainty analysis may be used with a non-metric criterion. Since uncertainties are dimensionless (using no metric), however, uncertainty analysis has a generality which may make it useful even when variances can be computed.


Covariance Public Policy Predictor Variable Variance Analysis Statistical Theory 
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Copyright information

© Psychometric Society 1956

Authors and Affiliations

  • W. R. Garner
    • 1
  • William J. McGill
    • 2
  1. 1.The Johns Hopkins UniversityUSA
  2. 2.Massachusetts Institute of TechnologyUSA

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