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Chi-Square Goodness of Fit: A Failure Rate Perspective

Published online by Cambridge University Press:  27 July 2009

Mark Brown  and
Marcia H. Flicker
Mark Brown
Affiliation:
Department of Mathematics The City College, CUNY New York, New York 10031
Marcia H. Flicker
Affiliation:
Graduate School of Business Administration Fordham University Bronx, New York 10458
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Abstract

Employing a failure rate approach, we propose a test statistic, , for the classic goodness-of-fit problem. It is then shown that a variation of , obtained by replacing observed variances by expected variances (an unwise change in our point of view), leads to the classical test statistic, x2. We argue that should be better approximated by a chi-square distribution, and thus employing , the true p−values should be closer to the nominal p−values than under x2 Various other comparisons of the two tests are made.

Type
Articles
Information
Probability in the Engineering and Informational Sciences , Volume 5 , Issue 3 , July 1991 , pp. 273 - 284
Copyright
Copyright © Cambridge University Press 1991

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References

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