I think the independence tag should be split in two (or something): One for independent data the other for independent variables. These are often confusing.
In regression, variables are rarely independent. If you have a balanced experiment design, they can be made independent and uncorrelated (assuming you have no missing data). In pretty much every other situation, including every observational study (and that's what people usually come to this site with), the regressors are correlated, and hence cannot be said to be independent. While I am totally fine referring to the response variable as the "dependent variable", I deliberately avoid the parallel, and always refer to the regressors as "explanatory variables".
If we can help the utterly confused readers of the site, we should do this. I am in no position to enforce my idiosyncratic terminology use on everybody, but I would suggest rethinking what the
independent variables may refer to.
Oh yes, the factors that come out of principal component analysis are uncorrelated (and hence independent if they are normal). And there's the method of independent component analysis, properly tagged
This is a bit of a repeat of the answer I posted here:
Error tag is ambiguous
...but we should really consider ending the use of the ambiguous tag and moving to new ones.
The new tag terms should not fight users, though. Many, many people use the term "independent variable", so you will have a constant battle on your hands if you try to enforce the exclusive use of predictor. "independent variable" and "predictor (variable)" are synonyms, so the tags should match that.
[independent variables]), and
Doing it this way will make the re-tagging job easier, leaving
[independence] as the tag to mean "I need a new tag".
Most importantly, whenever users start typing in "independen...", they will find a tag that matches what they want.