There is a more serious point arising from
slips like this: why do people cling to this
terminology? Not only are "dependent" and
"independent" already burdened with other
mathematical and statistical meanings, they are close
enough to be rather easy confused.
I acknowledge that there seems to be no consensus
either within or across disciplines on
good terminology, but that lack of consensus cuts
both ways: it means you can tie your flag to _one_ good
terminology (and then argue it out with
bosses, referees and editors). With (e.g.)
"response" and "predictors" or "covariates"
the chance of getting confused is much less.
Let me stress the "(e.g.)": I am just saying
this is a terminology I like better than
dependent and independent variables. Others
will differ, but I'd still like to hear
what the defence for "dependent" and "independent"
is, other than that it is still common.
Nick
[email protected]
[email protected]
>
> Ooops!
> >>> I have in mind the case where a lot of dependent
> variables are involved.
> I mean: independent.
>
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