Figure 15

How the Benjamini and Hochberg method works. This method is used to decide which P values in a set of many are low enough to be defined to be 'significant'. The P values are ranked from large to small. The ranks are plotted on the X axis, with the actual P values plotted on the Y axis. The dotted line shows the expectation if in fact all null hypotheses are true – 50% of the P values are less than 0.5, 25% are less than 0.25, etc. The solid line shows the Benjamini-Hochberg threshold for declaring a P value to be significant. It is defined by multiplying the dotted line by a fraction Q (here set to 1%). When the P value is lower than that threshold, that P value and all lower P values are defined to denote 'statistically significant' differences.