A simple test (QP-test) for the simultaneous detection of two outliers among extreme values of small data sets is described. This test is analogous and complements Dixon's classic Q-test. It is based on the probability distribution of the product of two Qexpvalues (QP: quotient product). Each Qexpvalue is calculated from the data set considering the presence of one and ignoring the presence of the other suspect value. Critical QP-values, calculated by a stochastic (a Monte-Carlo) procedure, are given for data sets containing 5 to 16 observations (replicates) at 0.90, 0.95, and 0.99 confidence levels. Based on the same principle, tests for the simultaneous detection of more than two outliers can be readily designed.