> In article <[EMAIL PROTECTED]>, > Glen <[EMAIL PROTECTED]> wrote: > > You cannot CHECK this, but you can TEST it. One problem is that > there are an infinite number of tests, and you can be sure that > some of them will fail, even if the sample is really iid. > > There are many situations in which this is done.
So (1) how can we always assume that? For example, I get a set of sample data by obeservation, then I assume i.i.d, then I can draw very far conclusions from these data involving some complex calculations; (2) could you give me some pointers to the books discussing this topic? Thanks, Zhutou . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
