Dixon's Q test

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In statistics, Dixon's Q test, or simply the Q test, is used for identification and rejection of outliers. This assumes normal distribution and per Dean and Dixon, and others, 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 = \frac{\text{gap}}{\text{range}}

Where gap is the absolute difference between the outlier in question and the closest number to it. If Q > Qtable, where Qtable is a reference value corresponding to the sample size and confidence level, then reject the questionable point. Note that only one point may be rejected from a data set using a Q test.

Example[edit]

Consider the data set:

0.189,\ 0.167,\ 0.187,\ 0.183,\ 0.186,\ 0.182,\ 0.181,\ 0.184,\ 0.181,\ 0.177 \,

Now rearrange in increasing order:

0.167,\ 0.177,\ 0.181,\ 0.181,\ 0.182,\ 0.183,\ 0.184,\ 0.186,\ 0.187,\ 0.189 \,

We hypothesize 0.167 is an outlier. Calculate Q:

Q=\frac{\text{gap}}{\text{range}} = \frac{0.177-0.167}{0.189-0.167}=0.455.

With 10 observations and at 90% confidence, Q = 0.455 > 0.412 = Qtable, so we conclude 0.167 is an outlier. However, at 95% confidence, Q = 0.455 < 0.466 = Qtable 0.167 is not considered an outlier. This means that for this example we can be 90% sure that 0.167 is an outlier, but we cannot be 95% sure.

Table[edit]

This table summarizes the limit values of the test.

Number of values:  3
4
5
6
7
8
9
10
Q90%:
0.941
0.765
0.642
0.560
0.507
0.468
0.437
0.412
Q95%:
0.970
0.829
0.710
0.625
0.568
0.526
0.493
0.466
Q99%:
0.994
0.926
0.821
0.740
0.680
0.634
0.598
0.568

See also[edit]

References[edit]

  • R. B. Dean and W. J. Dixon (1951) "Simplified Statistics for Small Numbers of Observations". Anal. Chem., 1951, 23 (4), 636–638. Abstract Full text PDF
  • Rorabacher, D.B. (1991) "Statistical Treatment for Rejection of Deviant Values: Critical Values of Dixon Q Parameter and Related Subrange Ratios at the 95 percent Confidence Level". Anal. Chem., 63 (2), 139–146. PDF (including larger tables of limit values)

External links[edit]

  • Test for Outliers Main page of GNU R's package 'outlier' including 'dixon.test' function.