The Difference Between Interaction and Association by Karen Grace-Martin.
From the post:
It’s really easy to mix up the concepts of association (a.k.a. correlation) and interaction. Or to assume if two variables interact, they must be associated. But it’s not actually true.
In statistics, they have different implications for the relationships among your variables, especially when the variables you’re talking about are predictors in a regression or ANOVA model.
Association
Association between two variables means the values of one variable relate in some way to the values of the other. Association is usually measured by correlation for two continuous variables and by cross tabulation and a Chi-square test for two categorical variables.
Unfortunately, there is no nice, descriptive measure for association between one categorical and one continuous variable, but either one-way analysis of variance or logistic regression can test an association (depending upon whether you think of the categorical variable as the independent or the dependent variable).
Essentially, association means the values of one variable generally co-occur with certain values of the other.
Interaction
Interaction is different. Whether two variables are associated says nothing about whether they interact in their effect on a third variable. Likewise, if two variables interact, they may or may not be associated.
An interaction between two variables means the effect of one of those variables on a third variable is not constant—the effect differs at different values of the other.
You will most likely be using statistics or at least discussing topic maps with analysts who use statistics so be prepared to distinguish “association” in the statistics sense from association when you use it in the topic maps sense. They are pronounced the same way. 😉
Depending upon the subject matter of your topic map, you may well be describing “interaction,” but again, not in the sense that Karen illustrates in her post.
The world of semantics is a big place so be careful out there.