I think this extends to jargon from scientific fields in general–e.g. "on the margin" from economics, "failure mode" from engineering, "significant" vs "substantial" (statistics), "system 1/system 2" (psychology), etc.
This is true, but mathematical jargon is more broadly applicable. (Though at this level of detail I would roll stats in with probabilty and hence pretend it is part of maths).
I've been a physicist and am now a software engineer. I can use the maths based jargon in both those fields, but not vice versa.
That's partly because everyone in a STEM field had to learn at least some maths. But more importantly: maths is about the logical interconnection of things, while the things themselves are substitutable. So it is no suprise that its jargon can be applied in many fields.
Significant, as in "statistically significant", usually that you've got sufficient evidence to conclude that your result is not simply due to random chance.
Substantial means that your result is big enough to have any practical import. In other words, is there any substance to the result?
For an example of a result that is significant but not substantial, suppose you find after surveying millions of people that members of demographic group X score 1/10 point higher than average on an IQ test.
For an example of a result that is substantial but not significant, sales figures are often so variable that it's impossible to determine with confidence whether even a 100% jump in revenues is due to a recent ad campaign or just a random fluke.
