I have six scatterplots (such as the one below) that show an insignificant interaction of the factor (X2) (e.g. gender, age, education etc.) with the predictor (X1) on Y. (X1 is significant.)
The simplest interpretation is that as X1 increases, Y increases for both levels of the factor (in this case, males and females). In other words, gender does not affect the relationship between X1 and Y and the difference in slope is due to sampling error.
These two statements apply to all other factors (e.g. age, which has three categories; education, which has three levels etc.).
One option is to present the six scatterplots and repeat the above statements as explanation. However, this seems tedious.
Is there a better (and succint way) of presenting these findings?
(I guess this is not a statistical question but it certainly relates to data analysis and interpretation!)