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dc.contributor.authorGiloni, Avi-
dc.contributor.authorSeshadri, Sridhar-
dc.contributor.authorSimonoff, Jeffrey S.-
dc.date.accessioned2008-05-25T15:22:53Z-
dc.date.available2008-05-25T15:22:53Z-
dc.date.issued2005-05-
dc.identifier.urihttp://hdl.handle.net/2451/26312-
dc.description.abstractWe discuss the use of robust analysis of variance (ANOVA) techniques as applied to quality engineering. ANOVA is the cornerstone for uncovering the effects of design factors on performance. Our goal is to utilize methodologies that yield similar results to standard methods when the underlying assumptions are satisfied, but also are relatively unaffected by outliers (observations that are inconsistent with the general pattern in the data). We do this by utilizing statistical software to implement robust ANOVA methods, which are no more difficult to perform than ordinary ANOVA. We study several examples to illustrate how using standard techniques can lead to misleading inferences about the process being examined, which are avoided when using a robust analysis. We further demonstrate that assessments of the importance of factors for quality design can be seriously compromised when utilizing standard methods as opposed to robust methods.en
dc.languageEnglishEN
dc.language.isoen_USen
dc.publisherStern School of Business, New York Universityen
dc.relation.ispartofseriesSOR-2005-4en
dc.titleRobust Analysis of Variance: Process Design and Quality Improvementen
dc.typeWorking Paperen
dc.description.seriesStatistics Working Papers SeriesEN
Appears in Collections:IOMS: Statistics Working Papers

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