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Activity Number:
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76
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Type:
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Contributed
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Date/Time:
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Sunday, August 6, 2006 : 8:00 PM to 9:50 PM
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Sponsor:
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Section on Statistical Education
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| Abstract - #305981 |
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Title:
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Is It Normal? A Simulation Study of Properties of Some Normality Tests
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Author(s):
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Daniel M. Sultana*+ and Charlyn J. Suarez and Bruce E. Trumbo and Eric A. Suess
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Companies:
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California State University, East Bay and California State University, East Bay and California State University, East Bay and California State University, East Bay
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Address:
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26970 Hayward Blvd., Apt. 102, Hayward, CA, 94542,
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Keywords:
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normality test ; R language ; Anderson-Darling ; Shapiro-Wilk ; Cramer-von Mises ; Kolmogorov-Smirnov
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Abstract:
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Statistical packages can perform several different goodness-of-fit tests of normality. We consider the tests of Anderson-Darling, Shapiro-Wilk, Cramer- von Mises, and Kolmogorov-Smirnov. For a given dataset these tests sometimes lead to different conclusions about normality, possibly leaving students and practitioners confused about which test to believe. We use the statistical package R to simulate normal and nonnormal data and to compare behaviors of these four tests. Specifically, we explore differences among the tests in several ways, focusing on reasons for their disagreement, on their relative power for several kinds of nonnormal data, and effects of using the tests in combination (for example, in terms of maximum and minimum P-values of several tests). Methods and R code are at an appropriate level for classroom use.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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