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16.7: Critical Values for Grubb's Test

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    220804
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    The following table provides critical values for \(G(\alpha, n)\), where \(\alpha\) is the probability of incorrectly rejecting the suspected outlier and n is the number of samples in the data set. There are several versions of Grubb’s Test, each of which calculates a value for Gij where i is the number of suspected outliers on one end of the data set and j is the number of suspected outliers on the opposite end of the data set. The critical values for G given here are for a single outlier, G10, where

    \[G_\text{exp} = G_{10} = \frac {|X_{out} - \overline{X}|} {s} \nonumber\]

    The suspected outlier is rejected if Gexp is greater than \(G(\alpha, n)\).

    Table \(\PageIndex{1}\): Critical Values for the Grubb's Test
    \(\frac {\alpha \ce{->}} {n \ce{ v }}\) 0.05 0.01
    3 1.155 1.155
    4 1.481 1.496
    5 1.715 1.764
    6 1.887 1.973
    7 2.202 2.139
    8 2.126 2.274
    9 2.215 2.387
    10 2.290 2.482
    11 2.355 2.564
    12 2.412 2.636
    13 2.462 2.699
    14 2.507 2.755
    15 2.549 2.755

    This page titled 16.7: Critical Values for Grubb's Test is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by David Harvey.

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