ASQ

Exclusive Content & Downloads from ASQ

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

Summary: (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.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

Subscribe to Journal of Quality Technology

Access this and ALL OTHER Journal of Quality Technology online articles. You'll also receive the print version by mail.

  • Topics: Statistics, Customer Satisfaction and Value, Inspection
  • Keywords: Statistics,Customers,Measurement error,Inspection
  • Author: Mee, Robert W.; Owen, D. B.; Shyu, Jyh-Cherng
  • Journal: Journal of Quality Technology