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The Relation between Information and Variance Analyses

Published online by Cambridge University Press:  01 January 2025

W. R. Garner  and
William J. McGill
W. R. Garner
Affiliation:
The Johns Hopkins University
William J. McGill
Affiliation:
Massachusetts Institute of Technology
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Abstract

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.

Type
Original Paper
Information
Psychometrika , Volume 21 , Issue 3 , September 1956 , pp. 219 - 228
Copyright
Copyright © 1956 The Psychometric Society

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Footnotes

*

The work of the senior author was supported by Contract N5ori-166, Task Order 1, between the U.S. Office of Naval Research and The Johns Hopkins University. This is Report No. 166-I-192, Project Designation No. NR 145-089, under that contract.

References

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