Using Permutation Tests to Reduce Type I and II Errors for Small Ruminant Research

Although parametric tests (F or t) are considerably effective, these are sometimes ineffective when the assumptions needed by model are not provided. In such a case, permutation test unaffected by the assumptions can be applied as a non-parametric method. It has been observed by citing an example that permutation test produces more reliable results than one-way ANOVA in terms of type I error rate and power of the test and permutation test is recommended in order to avoid type I and II errors and to prevent the potential profit lost.