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In statistics, the Q test a nonparametric statistical test used for identification and rejection of outliers. This test should be used sparingly and never more than once in a data set. To apply a Q test for bad data, arrange the data in order of increasing values and calculate Q as defined:
Q = Qgap/Qrange
Where Qgap is the absolute difference between the outlier in question and the closest number to it. If Qcalculated > Qtable then reject the questionable point.
Table[edit | edit source]
|Number of values:|| 3
Example[edit | edit source]
For the data:
Arranged in increasing order:
Outlier is 0.169. Calculate Q:
With 10 observations at 90% confidence, Qcalculated < Qtable. Therefore keep 0.169 at 90% confidence.
See also[edit | edit source]
References[edit | edit source]
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