I have used a 2×3 mixed between-within subjects ANOVA to assess the impact of three feedback conditions (Grade, Comment and No Feedback) on participants’ scores on the Specific-Self Efficacy Scale on two occasions, pre- and post- task.
I did not get a significant main effect but I did get a significant interaction effect.
My tutor has told me that I can interpret the results from the interaction graph alone and
that there is no need to run tests to see if there are significant differences between pre and post task scores in each of the feedback conditions.
However, when discussing these results in my manuscript, I do not feel confident in relying on a graph alone.
Is it appropriate to only use the interaction graph to discuss results or we you recommend running some paired samples t-tests?
Thank you for taking the time to read my query!
Best Answer
I like your tutor, but many people will not. The question of effect size (which shows up on a graph) vs. statistical significance (which you get as part of the output from a test) has been discussed a lot; I am strongly on the effect size side, but others differ (and not completely unreasonably, either).
However, it is often nice to be able to put some precise numbers in the text and it is hard to get those from a graph alone.