Robust Analysis of Variance: Process Design and Quality Improvement

23 Pages Posted: 3 Nov 2008

See all articles by Avi Giloni

Avi Giloni

Independent

Sridhar Seshadri

University of Illinois at Urbana Champaign; Indian School of Business

Jeffrey S. Simonoff

New York University (NYU) - Leonard N. Stern School of Business; New York University (NYU) - Department of Information, Operations, and Management Sciences

Date Written: May 2005

Abstract

We 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.

Suggested Citation

Giloni, Avi and Seshadri, Sridhar and Simonoff, Jeffrey S., Robust Analysis of Variance: Process Design and Quality Improvement (May 2005). NYU Working Paper No. SOR-2005-4, Available at SSRN: https://ssrn.com/abstract=1293159

Sridhar Seshadri

University of Illinois at Urbana Champaign ( email )

1206 South Sixth Street
Champaign, IL 61820
United States

Indian School of Business ( email )

Hyderabad, Gachibowli 500 019
India

Jeffrey S. Simonoff

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

New York University (NYU) - Department of Information, Operations, and Management Sciences

44 West Fourth Street
New York, NY 10012
United States

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