Re: [Phys-l] Basic statistics

[Bernard Cleyet <bernardcleyet@redshift.com>]

I think you two are "talking (writing) past each other".    One is a 
single distrib. tother several independent.  Furthermore, Wiki, claims 
that the Chi-square also does tend towards normalcy, but VERY slowly, as 
the # of DOF increases.

http://en.wikipedia.org/wiki/Chi-square_distribution


bc





Jack Uretsky wrote:

> As already pointed out, the central limit theorem does not apply to all 
> distributions.  You must state the theorem carefully.  In the case of the 
> chi-square distribution it is easy to demonstrate by example with MathCad 
> or a similar program that the large N limit is not Gaussian.
> 					Regards,
> 						Jack
>
> On Fri, 10 Nov 2006, Polvani, Donald G. wrote:
>
>  
>
> > Jack Uretsky wrote:
> >
> >    
> >
> > > This is a misconception. There are many distributions that become
> > >      
> > Gaussian in the large N limit, but not all.
> >    
> >
> > > The chi-squared distribution is an example of one that does not.
> > >      
> > However, for the SUM of independent, identically distributed random
> > variables, each with mean mu and variance sigma^2, the central limit
> > theorem tells us that the distribution (of the sum) tends to a Gaussian
> > as N approaches infinity.
> >
> > Don Polvani
> > Northrop Grumman Corp.
> > Undersea Systems
> > Annapolis, MD 21404
> > _______________________________________________
> > Forum for Physics Educators
> > Phys-l@carnot.physics.buffalo.edu
> > https://carnot.physics.buffalo.edu/mailman/listinfo/phys-l
> >
> >    
>
>