You can also demonstrate the central limit theorem in Stata
type "findit central limit theorem "
brings up:
TITLE
clt. Central limit theorem Demonstration
DESCRIPTION/AUTHOR(S)
Michael N. Mitchell
Statistical Computing and Consulting
UCLA Academic Technology Services
[email protected]
STATA ado and hlp files in the package
Scott Merryman
----- Original Message -----
From: "Gene Fisher" <[email protected]>
To: <[email protected]>
Sent: Sunday, July 21, 2002 1:43 PM
Subject: RE: st: Re: normal distributions
> Victor,
> This site may help your intuition:
>
http://www.math.csusb.edu/faculty/stanton/m262/central_limit_theorem/clt.htm
> l. Also look at this site:
> http://www.statisticalengineering.com/central_limit_theorem.htm. There
are
> ever so many more references you can obtain from a search of Central Limit
> Theorem on Google.
>
> Gene Fisher
> Department of Sociology
> University of Massachusetts
> Thompson Hall, 200 Hicks Way
> Amherst, MA 01003-9277
> (413) 545-4056; [email protected]
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]On Behalf Of [email protected]
> Sent: Sunday, July 21, 2002 3:28 PM
> To: [email protected]
> Subject: Re: st: Re: normal distributions
>
> Thanks,but that is why I am concerned about my inability to get its
> intuition.It seems contradictory to me,that an inherently negatively or
> positively skewed population distribution,could be normalised,by enlarging
> the
> sample size.If anything,that should retrace the skewness and not normalize
> the
> skewness.
> Victor
>
>
> Quoting David Greenberg <[email protected]>:
>
> > This topic is discussed in virtually every introductory statistics
> > textbook. David Greenberg, Sociology Department, New York University.
> >
> > ----- Original Message -----
> > From: [email protected]
> > Date: Sunday, July 21, 2002 1:33 pm
> > Subject: st: Re: normal distributions
> >
> > > Dear subscribers,
> > > can anyone help me understand how is it that for types of
> > > population
> > > distributions that are non-normal the sampling distribution of
> > > Xbar is
> > > approximately normal for sufficiently large samples.
> > > Thanks Victor Michael Zammit
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/support/faqs/res/findit.html
> > > * http://www.stata.com/support/statalist/faq
> > > * http://www.ats.ucla.edu/stat/stata/
> > >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
