Premium
An alternative to the analysis of variance for reliability data
Author(s) -
Edgeman Rick L.
Publication year - 1990
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.4680060307
Subject(s) - inverse gaussian distribution , variance (accounting) , skew , reliability (semiconductor) , statistics , gaussian , computer science , econometrics , one way analysis of variance , skew normal distribution , normal inverse gaussian distribution , mathematics , distribution (mathematics) , analysis of variance , normal distribution , gaussian process , gaussian random field , mathematical analysis , telecommunications , power (physics) , physics , accounting , quantum mechanics , business
Though the analysis of variance is a commonly applied method for testing for differences between means of several processes, it is based in part on the assumption that the processes give rise to output that is normally distributed on the measured variable. Reliability and life test studies frequently give birth to data that exhibit clear skew, and application of the analysis of variance is questionable in such cases. A method referred to as analysis of reciprocals, which is based on an assumed inverse Gaussian distribution, provides an alternative to the analysis of variance in these instances. With applications in a variety of functional areas, including reliability and life testing, the inverse Gaussian distribution is able to accommodate substantial skew. It is hoped that this exposition will increase awareness of both the inverse Gaussian distribution and data analysis methods that are based on this distribution.