Article ID Journal Published Year Pages File Type
1245672 Talanta 2006 4 Pages PDF
Abstract

Common significance tests carried out using statistical software packages usually return to the user the probability p of type I error as the result. Based on p and the preset confidence level the user will decide on the acceptance or the rejection of the associated null hypothesis. Dixon's test (Q-test) is commonly used for the detection of an outlier within a set of N observations (typically: N = 3–12). Q-test can only be applied by comparing the experimental value of the statistic Q with tabulated critical Q-values corresponding to some standard values of p. Hence, for a given value of Q and a number of observations, N, the user knows only the range and not the value of the associated probability p of type I error (erroneous rejection). This is due to the lack of explicit expressions of the form p = F(Q,N). In this work, a simple stochastic (Monte Carlo) approach is presented for the estimation of p corresponding to a given experimental value of Q and size N of the data set. In addition, based on Dixon's equations, explicit expressions of p are given for N = 3 and 4.

Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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