# Insignificant vs. Non-significant

Like 99.8% of the people in psychology departments, I hate teaching statistics, in large part because it’s boring as hell, for both the instructors and the students, but also because students have a hell of a time grasping it, and that makes for some really painful interactions. Part of the problem, I think, is that the way we talk about statistics wasn’t designed to facilitate undergraduate instruction. And to see this, you need look no further than the concept of statistical significant.

First of all, whose idea was it to refer to it as significance? I mean, the first thing you tell students is that a statistically significant result doesn’t mean that the result is significant in any meaningful sense (say, practically), but of course, they never get that, because it’s confusing. And as a result, they constantly refer to null results as “insignificant.” But they’re not “insignificant,” or at least, they aren’t necessarily so. They might very well be significant — a null result in a study seeking to find a connection between autism and vaccines, say, could be very significant, especially for those being sued by the families of autistic children. So I tell my students, over and over and over and over and over again, to refer to the results of statistical tests that don’t achieve statistical significance as “non-significant.” But “non-significant” is not a word anybody uses in any context, ever, except in statistics. So they say, “OK, non-significant not insignificant, got it,” and then in every paper and every presentation, they write or say, “Our results were insignificant.” Aaaaaaaaaaaaahhhhhhhhhh! Sometimes, you can almost see their brains trying to convince their mouths to say, “non-significant,” but their mouths refuse, and “insignificant” comes out. It’s just plain frustrating.

Now, I’d be happy to do away with the concept of statistical significance altogether, but I’m not the one who makes these sorts of decisions, so if we have to keep it, and teach it, can we please call it something else? How ’bout, “statistically good enough for me to publish,” “statistically better for us than if our p-value had been greater than .05/.01/.001,” or “statistically gnarly?” ‘Cause this “significance” shit ain’t working.

rant>