Confidence Bounds for Misclassification Probabilities Based on Data Subject to Measurement Error


Mee, Robert W.; Owen, D. B.; Shyu, Jyh-Cherng   (1986, ASQC)   University of South Alabama; Southern Methodist University; American Family Life Assurance of Columbus, Georgia

Journal of Quality Technology    Vol. 18    No. 1
QICID: 5554    January 1986    pp. 29-40
List $10.00
Member $5.00

You will need to be signed in.
New to ASQ? Register here.

Article Abstract

(This paper was presented at the Journal of Quality Technology Session at the 29th Annual Fall Technical Conference of the Chemical and Process Industries Division of the American Society for Quality Control and Section on Physical and Engineering Sciences of the American Statistical Association in Corning, New York, October 24-25, 1985).When test measurements of items differ from the true product values because of random measurement error it is possible to reject satisfactory items and to accept inferior ones. Confidence bounds for these misclassification probabilities are obtained, assuming that the true product values and measurement errors are independently distributed normal variates. Both joint and conditional probabilities are investigated. These probabilities are functions of the proportion of measurement error variability (relative to the total variance). Methods are presented for situations where this proportion is known or is estimated from sample data. Tables are provided to simplify the computations required.


Statistics,Customers,Measurement error,Inspection

Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers

ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.