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Downloadable! grubbs test (Grubbs, 1969 and Stefansky, 1972) can be used to detect outliers in a data set, either creating a new variable (equal to 1 if the observation is an outlier and 0 otherwise) or dropping outliers out of the data set. ... Keywords: Grubbs; outliers; maximum normed residual test;
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Downloadable (with restrictions)! No abstract is available for this item. ... Otero, Jesus & Smith, Jeremy, 2003. "The KPSS Test with Outliers," The Warwick Economics Research Paper Series (TWERPS) 690, University of Warwick, Department of Economics. [Downloadable!]
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Kurtosis provides a good omnibus test for outliers in small samples. ... CONCLUSIONS: Where the number of outliers is unknown the kurtosis test for outliers is more versatile than the Grubbs test as it has greater power where there is more than one outlier, a similar power when there is just one outlier,
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The software in your system uses two features to identify "outliers". One indicator is called the "Global ‘H’ and the other is the "T test". A discussion of how "Global H" and "T Test" work is beyond the scope of these instructions and can be obtained from the suppliers of the ISI/NIRS software.
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Grubbs' test for outliers - Wikipedia, the free encyclopedia
Many statistical techniques are sensitive to the presence of outliers. For example, simple calculations of the mean and standard deviation may be distorted by a single grossly inaccurate data point. C...
en.wikipedia.org/wiki/Grubbs'_test_for_outliers |
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Date: 09/11/2001 at 11:36:58 From: Doctor Jubal Subject: Re: Spotting outliers Hi Stu, Thanks for writing Dr. Math. There are a number of fairly simple ways to test for outliers. I'll describe three, and maybe one of them is the one you were thinking of.
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Rosner s Test for detecting up to k outliers can be used when the number of data points is 25 or more. This test identifies outliers that are both high and low, it is therefore always two-tailed (Gibbons, 1994). The data are ranked in ascending order and the mean and standard deviation are determined.
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