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Fitting Learning Curves with Orthogonal Polynomials

Authors: Mark A. Sabol;

Fitting Learning Curves with Orthogonal Polynomials

Abstract

Abstract : A FORTRAN program that generates orthogonal polynomials is listed. These polynomials can be used to analyze learning curves into components that can then be tested separately for significance (planned comparisons). The program is appropriate to situations in which the data are obtained from equally spaced intervals, as is naturally the case when the independent variable is trials, and also to situations involving unequal intervals (e.g., when data are available from the first, second, fourth, and eighth trials only). A demonstration of the component analysis is provided for both the equal interval and unequal interval situation. These analyses result in best-fit curves that reflect only those components that have proved significant. An appendix lists all orthogonal polynomials for situations with equal intervals and up to 20 trials. This listing greatly extends those currently available in the statistical literature, which provide all polynomials only for situations with up to 7 trials.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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