On Mon, 01 Dec 2003 02:33:13 GMT, "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.

I did not notice this at first reading -- you say that you 
want to compare the variances, too.  

Variance differences make it difficult to do tests of means,
and more, it can make it difficult to interpret them.  The 
group with REALLY big variance will have the extreme
scores in both directions:  Otherwise, you are talking 
about something that I would consider to be confounded
with *scaling* questions.    Are you absolutely sure that
you are interested in the difference of the 'arithmetic 
mean'? and not the 'central tendency', or the superiority
at one end or the other?


So, look at your plots.  Similar?  Shifted?  Expanded?
You could do several varieties of tests and see if they
all come out the same, as a cheap version of 'testing for
normality.'   That's the easiest step, when you don't want
to commit to anything about the numbers.

Oh, the basic, simple, usual nonparametric tests that use
ranks  have assumptions that are almost as harsh as those
of the t-test, so you can't really opt out of all thinking merely
by employing that rank transform. 


> 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 there are no outliers, then the t-test is pretty robust
for the means.  A test on ranks is not exactly a test on means.
 
> 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?

As Dave says -- if you have a sequence where the word 
'sequence'  is meaningful, then you have to take that into
account; simple zero-order  correlation (or regression) gives 
bogus values and tests when there is dependency. 


-- 
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
"Taxes are the price we pay for civilization." 
.
.
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