The outcomes of your experiments may not always be consistent. For example, when you sample the people who say that they prefer Chinitos, this may actually depend on which Chinito they are referring to. Another example is in court where there is interaction between the judge and the case they are handling. Because of judge-case interaction, different judges may carry out different sentences for the same case.
In the same way, statistical interaction is important in research. It doesn’t mean that we already know the dependent variable if we know the independent variable. We can know through the Analysis of Variance Test (ANOVA) whether statistical interaction is significant, from which we need to analyze and interpret the effect statistical interaction on results.
Remember
Just because we know the independent variable, we cannot exactly know or predict the dependent variable based on this alone.
Statistical interaction is important as we have to see whether variables have an effect on each other when it comes to the results.
Tanim Talino 