In article <[EMAIL PROTECTED]>,
jackson marshmallow <[EMAIL PROTECTED]> wrote:
>Hello everyone,

>I hope I can get simple answers to these questions... I need to solve a
>couple of practical problems and I'm new to statistics...

>1) Two samples of are given and I need to compare their means and variances.
>The distribution of the population is unknown. Can I use the F-test and the
>t-test? Is it necessary that the sample _means_ have a Gaussian
>distribution? Is it sufficient? Maybe I misunderstand something here...

If the population is not normal, the sample means CANNOT
have a normal distribution.  However, it gets closer to
normal with increasing sample size.

The t-test is approximate if the data is not normal.  Is
the error in the significance levels more important than
using bad levels in the first place?  As for the F-test,
this is quite sensitive to the distribution.  Again, just
what are you after?  Do you want means and variances at
all?  Or do you want something else?

If you want to test equality of distributions, a nonparametic
test might be a good idea.  As you express an interest in
comparing variances, I would suggest the Kuiper test rather
than the Kolmogorov-Smirnov test.  It is almost as good as
a test for location, and much better for scale.  For a 
decision understanding of this, I suggest my paper with
Sethuraman in Sankhya 1965, and my paper in the Sixth
Berkeley Symposium.

>2) I need to calculate the significance of correlation between two
>sequences. I would actually prefer to use randomization, but the sequences
>may be too short. Another option is to perform linear regression and
>calculate the significance of the slope using a t-test (?). When is it
>valid?

>Again, I'm looking for simple answers, if they exist... Thanks in advance!

If there is not a problem of dependence between different 
points, the Spearman rank correlation or Kendall tau might
be a good idea.


-- 
This address is for information only.  I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Department of Statistics, Purdue University
[EMAIL PROTECTED]         Phone: (765)494-6054   FAX: (765)494-0558
.
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