Linda <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> Hi!
>
> I have some experimental data collected and can be grouped into 2
> variables, X and Y. One is the dependent variable (Y) and the other is
> an independent variable (X). What test shall I made to check whether
> there can be expressed as independent or not??
There are so many ways variables can fail to be independent that a truly
general test usually won't have good power against specific alternatives.
Essentially you'd need to estimate f(Y|X) somehow and compare it to f(Y) (also
estimated somehow). I have no advice on the best way to tackle the test, since
it depends on how you do the estimation (and you need to keep in mind that
since the two distributions are estimated from the same data, they are not
independent).
If X&Y are categorical, there are a number of general tests of independence, of
which the usual Pearson chi-squared test of independence is the best known.
It's much better if you can specify the kind of alternatives you care about
most, and the more specific the better. For example, one thing that would help
to nail it down a little would be to say you only care about relationship in
the mean - i.e. you need to detect if E(Y|X) = E(Y). This is still very
general, but it's better. If you're only interested in monotonic relationships,
it's easier still.
But you need to clarify what you require.
Glen
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