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- W69868882 abstract "Observations which deviate strongly from the main part of the data, usually lebeled as ’outliers’ are troublesome and may cause completely misleading results. Therefore, the solitariness of outliers is important for quality assurance. It is desirable to derive such approaches in a systematic manner from general principles and guidlines rather than human decision making or simply plotting the data. A test for outliers of normally distributed data has been developed by J. W. Dixon [1]. The present study uses the same idea by arranging the data set in ascending order for the particular case where samples are comming out of Uniform distribution. Percentage points are tabulated for testing hypothesis and constructing confidence intervals for different significance levels." @default.
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- W69868882 date "2009-01-01" @default.
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- W69868882 title "Outliers in Uniform Distribution" @default.
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