Abstract #301123

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JSM 2003 Abstract #301123
Activity Number: 50
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Section on Quality & Productivity
Abstract - #301123
Title: The Simplest Two Sample Scale Test: Count Five
Author(s): Richard N. McGrath*+ and Bai-Yau Yeh
Companies: Bowling Green State University and Bowling Green State University
Address: 360 Business Administration Bldg., Bowling Green, OH, 43403-0001,
Keywords: dispersion ; variance ; nonparametric ; scale ; two samples
Abstract:

It is well-known that the common "F-test" for testing equality of variances is very sensitive to the normality assumption. Yet, most introductory statistics books do not stress this sensitivity or suggest any alternative procedures. Many scale tests have been developed that do not make the normality assumption, but they often require published tables or rely on asymptotic approximations. We discuss a very simple test that compares extreme points of one sample to another. With equal sample sizes, if one sample has the five most extreme points, it is concluded that that population has a larger scale parameter. Adaptations are provided for unequal sample sizes. We believe the simplicity and robustness of this new test make it a viable alternative to the often misleading F test that dominates variance testing in introductory texts.

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