You need an interaction plot. This is a graph that will answer your question. The first link below should answer your questions and give examples. The book in the second link also discusses it and on p.67 gives R code for drawing it. feel free to contact me with questions. Best wishes, David

http://www.bing.com/search?pc=COSP&ptag=D071616-A0A14E5293D1943C986F&form=CONBDF&conlogo=CT3330954&q=interaction+plot+factorial+design

https://www.amazon.com/Analysis-Experiments-Chapman-Statistical-Science/dp/1439868131/ref=sr_1_1?ie=UTF8&qid=1487410817&sr=8-1&keywords=john+lawson+r

The significant interaction term indicates that the effect of one factor variable isn't uniform over the levels of the other factor variable. For an easy example, let's say profit is your dependent variable. If a conservative monetary policy led to increased profits in small businesses, but decreased profits in big businesses, then there would be an interaction effect of Mp x Sf on profit. It can be more subtle. If a conservative monetary policy leads to a small increase in profitability for small firms but a large increase in profitability for large firms, that's still a Mp x Sf interaction on profit.

As David Eugene Booth said, if there is a significant interaction, you want to make an interaction plot.

But also, you will want to do post-hoc testing, mean separation, or multiple comparisons of means, for the effect of the interaction. This will tell you which means are different from which other means.

For example, this is a plot of the interaction of Tribe and Location. Means sharing a letter are not significantly different.

http://rcompanion.org/handbook/images/image234.png

The interaction between "monetary policy" and "the size of a firm", for instance, is the degree of inconsistency of occurrence of one of the two variables at different levels of the other variable and vice versa. If this is significant, then at different firm sizes, monetary policy will not be the same and vice versa.