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Abstract
The robustness of two-sided tolerance limits for normal distributions is examined based on a computer simulation in which the Student's t and gamma distributions are used as generating models. Results indicate that the normal tolerance limits are sensitive to departures from normality when k-factors are selected for coverages in excess of 0.9. Reasonable robustness is achieved for coverages of 0.9, as long as the underlying distribution is not extremely heavy-tailed nor highly skewed.
Additional information
Notes on contributors
George C. Canavos
Dr. Canavos is an Associate Professor of Management Science, School of Business.
Ioannis A. Koutrouvelis
Dr. Koutrouvelis is an Associate Professor of Mathematical Sciences, College of Humanities and Sciences.
