Confidence intervals, stats modules?
Stephen Boulet
mean, standard deviation? Thanks.
-- Stephen
Duncan Smith
"Stephen Boulet" <ste...@theboulets.net> wrote in message
news:ug2r3aa...@corp.supernews.com...
> Are there any stats modules to calculate things like confidence intervals,
> mean, standard deviation? Thanks.
>
> -- Stephen
http://www.nmr.mgh.harvard.edu/Neural_Systems_Group/gary/python.html
Tim Churches
Gary's stats module is excellent and is probably sufficient for the uses
you
describe. There are also some elementary statistical functions in Konrad
Hinsen's
equally excellent Scientific Python package - see
http://starship.python.net/crew/hinsen/scientific.html
In fact, you could just use NumPy (Numerical Python) - have a look at
the MLab
module in NumPy (which is at http://www.pfdubois.com/numpy/ ).
However, if you are interested in more advanced statistical analysis
and/or in
drawing statistical graphs, then have a look at RPy, by Walter Moreira,
at http://rpy.sourceforge.net
RPy embeds the R stats environment within Python. R is good for most
things
statistical, from the elementary to the advanced and experimental, and
it does
truly beautiful graphics. It is a mature project backed by a number of
eminent
statisticians in five continents.
Note that R is multi-platform (see http://www.r-project.org ) but RPy
only
works under Linux and Unix (and Mac Os X, perhaps) at this stage. I
believe
a Windows version is in the works.
Tim C
Alan James Salmoni
have mean, stddev etc). I am working on it myself for my own stats
package, but it might be a few weeks as I am concentrating upon non
parametric stuff.
Alan.
Tim Churches
>
> Problem is that I don't think stats.py has confidence intervals (it does
> have mean, stddev etc). I am working on it myself for my own stats
> package, but it might be a few weeks as I am concentrating upon non
> parametric stuff.
Assuming your are talking about a normal variate, the stats.py module
has a function
for the sample std deviation but not, as far as I recall, for the
Student's t distribution,
which is needed to calculate confieence intervals where the popuation
std deviation is
unknown (which is most of the time).
Thus, I think that R, via RPy, is a better bet. R also has all the
machinery you need to
calculate confidence limits for non-normal variates too. Even simple
statistics only remain
"elementary" if you don't think too hard about them.
Tim C
> --
> http://mail.python.org/mailman/listinfo/python-list
Travis Oliphant
> Assuming your are talking about a normal variate, the stats.py module
> has a function
> for the sample std deviation but not, as far as I recall, for the
> Student's t distribution,
> which is needed to calculate confieence intervals where the popuation
> std deviation is
> unknown (which is most of the time).
The scipy.stats
module in scipy (www.scipy.org)
has Student's t distribution and many many others.
It could be used to compute confidence intervals.
Happy computing,
-Travis O.