Figure 20.

Worked example. Using the Benjamini and Hochberg method to detect outliers. A P value was determined for each point by computing a t ratio by dividing its residual by the RSDR, and computing a two-tailed P value from the t distribution. See Table 1. The P values are shown plotted against their rank. The dashed line shows what you'd expect to see if the P values are randomly scattered between 0 and 1. All but lowest two of the P values lie very close to this line. The solid line shows the cutoff when Q is set to 5%. Both of the points with the lowest P values (the two points furthest from the robust best-fit curves) are defined to be outliers. The dashed line shows the cutoff when Q is set to 1% as we suggest. Only one point is an outlier with this definition, which we choose to use.

Motulsky and Brown BMC Bioinformatics 2006 7:123   doi:10.1186/1471-2105-7-123
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