JSM 2005 - Toronto

Abstract #303066

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 29
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor: Section on Quality and Productivity
Abstract - #303066
Title: A Nonparametric Statistic for Joint Mean-Variance Quality Control
Author(s): J.D. Opdyke*+
Companies: DataMineIt
Address: 46 Tioga Way, Marblehead, MA, 01945, United States
Keywords: Quality control ; Statistical process control ; Six sigma ; Mean-variance ; Location-scale ; Telecommunications

For statistical process control, a number of single charts that jointly monitor both process mean and variability have been developed. For quality control-related hypothesis testing, however, there has been less analogous development of joint mean-variance tests; only one two-sample statistic known to this author has been designed specifically for the one-sided test of Ho: Mean1 < = Mean2 and Variance1 < = Variance2 vs. Ha: Mean1 > Mean2 OR Variance1 > Variance2 (Opdyke 2005). This paper further develops this statistic and demonstrates via Monte Carlo simulation that it always maintains good level control, it has good power under symmetry and moderate power under moderate asymmetry (for which a transformation is used), and it often has dramatically more power than the only proposed competitor. The statistic is easily implemented, and although initially designed for use in regulatory telecommunications, its range of application is as broad as the number of settings requiring a test of the joint hypotheses listed above.

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