<![CDATA[Factorial experimental designs involve more than one factor and what needs to be tested is the interaction between treatment factors in addition to the effects of each treatment factor itself. This study aims (a) to consider graphical line drawings as a reference for formulating conclusions that there is an interaction between the two treatment factors, and (b) to examine and follow up on the results of the analysis of variance in factorial experiments which conclude that the interaction between the two factors is significant, not to ignore the possibility of single factor variance dominating. . The research refers to the research data "Study of the Effect of Pellet organic Fertilizer from Municipal Waste on the Nutrient Content of Spinach (Amaranthus hybridus L)." the two single factors are significant, the graphic lines intersect a lot, the data presentation and interpretation refer to the combined treatment (b) the carotene content data in spinach vegetables, the interaction of the two treatment factors is significant, the two single factors are significant, the graphic lines are almost all parallel and almost intersect, so the data presentation and the interpretation of the PeOF raw material type factor refers to a single factor, (c) the data on the content of vitamin C in spinach vegetables, the interaction of the two treatment factors is significant, the two single factors are significant, the graphic lines are almost all not parallel, almost intersect, so the data presentation and the interpretation of the material type factor PeOF standard and urea application factor refer to a single factor. When using a factorial design, it is found that real interactions do not necessarily mean that the data presentation refers to the combined treatment. It is necessary to test further for the possibility that the diversity of single factors is more dominant so that the data presentation and conclusions refer to a single factor.]]>
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