To evaluate interaction is one of the most important objectives of fatorial experiments. In experiments with two factors A and B, with m and n levels of each factor, there are m x n possible interactions and (m-1)(n-1) degrees of freedom associated. Frequently just a part of these interactions contributes effectively to the sum of squares of interaction and must be interesting to evaluate them. The use of less rigorous level of significance for interpretation of the interaction "for experiment", in relation to sources of variation of the variance analysis, may catch important effect. One recommends the use of p = 0.25 for the interpretation of the effect of the interaction "for experiment" remaining usual p = 0.05 for effect "for comparisons". Even in the case of significant interactions, selected comparisons, instead of "cuts" only, may assist the interpretation of complex interactions.
Analysis of variance; interaction sliced; significance level
