JOURNAL OF APPLIED ANIMAL RESEARCH, cilt.32, sa.1, ss.69-72, 2007 (SCI-Expanded)
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.