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From |
"Scott Merryman" <merryman@icehouse.net> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Re: normal distributions |

Date |
Sun, 21 Jul 2002 13:58:17 -0600 |

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 mnm@ucla.edu STATA ado and hlp files in the package Scott Merryman ----- Original Message ----- From: "Gene Fisher" <fisher@soc.umass.edu> To: <statalist@hsphsun2.harvard.edu> 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; fisher@soc.umass.edu > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of kusi@yorku.ca > Sent: Sunday, July 21, 2002 3:28 PM > To: statalist@hsphsun2.harvard.edu > 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 <dg4@nyu.edu>: > > > This topic is discussed in virtually every introductory statistics > > textbook. David Greenberg, Sociology Department, New York University. > > > > ----- Original Message ----- > > From: kusi@yorku.ca > > 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/

**References**:**RE: st: Re: normal distributions***From:*"Gene Fisher" <fisher@soc.umass.edu>

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