[thanatropism]

The problem is not plain English, the problem is that you want to make claims that are more specific than your numbers allow you to.

"Correlation is a number in [-1,1] where -1 means predictably inversely related and 1 means predictably directly related". What is correlation 0.5? There isn't even an unique definition of "correlation", man.

The best thing you could do is to produce a table of correlation coefficients for comparison. That would communicate some qualitative nuance as to what a 0.5 correlation really means.

You can also try to do something like a bootstrap or kernel density or use a prior distribution to claim that the probability that increment dx leads to an increment of dy or more is... That's more technically involved, but satisfies your desire of saying something specific that correlation coefficients do not allow you to say.

[ordinaryperson]

Kernel density, bootstrap, using prior distribution, increment the derivative...all this stuff is so far above and beyond the ordinary person.

You and a couple of others have provided plenty of context for the serious data scientist who wants to understand the exact nature of the relationship between these two variables, but 99% of readers do not understand much less want to read about "kernel density".

Again, my challenge remains open: instead of complaining about inaccuracy, try to render the relationship in plain English.

[thanatropism]

There's no much that can be said. Your quantitative analysis is weak.

[ordinaryperson]

Lol. I was giving a basic intro for the 99% of readers who don't care about "kernel density" or controlling for output variables -- the fact that you conflate such an attempt with a "quantitative analysis" (which it was not) coupled with your unwillingness or inability to give a plain English description just proves my point.