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Statistical Methods for a Theory of Cue Learning

Published online by Cambridge University Press:  01 January 2025

Frank Restle*
Affiliation:
Michigan State University

Abstract

A theory of cue learning, which gives rise to a system of recurrent events in Feller's sense, is analyzed mathematically. The distribution of total errors and sampling distribution of mean errors are derived, and the learning curve is investigated. Maximum likelihood estimates of parameters and sampling variances of those estimates are derived. Likelihood ratio tests of the usual null hypotheses and approximate tests of goodness of fit of substantive hypotheses are developed. The distinguishing characteristic of these tests is that they are concerned with meaningful parameters of the learning process.

Type
Original Paper
Copyright
Copyright © 1961 The Psychometric Society

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Footnotes

*

This research was facilitated by the writer's tenure as Faculty Research Fellow, Social Science Research Council, 1959–1961.

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