How to interpret interaction effects when main effects are also significant


I am currently writing my thesis, and stumbled upon a problem. I am testing an hypothesis in which I examine an interaction effect. Unfortunately, both the main effect and the interaction effects are significant (see image below). Right now I don't know what to report. So my questions are:

- Is the interaction effect significant? (because the other 2 terms are also significant)
- How do I interpret this model?
- How do I report this? should I use the information from the main model (above the table) or only look at the information in the table?

Thank you very much for helping me, you are really saving me!

Kind regards,


PS: additional info: all variables are continuous, and I performed a simple linear regression. Hopefully this is enough info. But if not, I will give whatever info needed of course!

interaction table.png
Last edited:


Less is more. Stay pure. Stay poor.
If you are hypothesizing an interaction, then you are saying the effects of the main terms are conditional on each other. Thus you no longer care about the main terms, regardless if they are significant or not. You solely report the interaction term.