In my data set, I've run a 2-way ANOVA with interaction. Found the interaction term to be non-significant. I re-ran the ANOVA without the interaction, and got the results that both my explanatory variables are significant.

In essence, the resulting plot looks like this:

What would be an efficient way to recapitulate the statistical result on such a graph? Should I split the graphs by gender? By courses? Both?

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#### Best Answer

The resulting plot looks fine to me: You show that there is a main effect of class type: Calculus scores are higher than the other two. You also show the main effect of gender: Males tend to do better than females. And your insignificant moderation is also shown here: The pattern of males performing better than females is the same across all types of classes; the pattern of Calculus being higher than Algebra+Geom being higher than Algebra alone is the same for both men and women.

The problem with splitting the graphs by gender or by course is that you wouldn't be able to see the main effects of gender or course on these new graphs—information that you want to present to the reader. I think the figure you have captures your results nicely.

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