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From |
kusi@yorku.ca |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: entering data |

Date |
Sun, 21 Jul 2002 17:47:21 -0400 |

Dear listers, can anyone help me with the following awkward task. I have generated variables a and b ,so as to form a triangular distribution,hence a non -normal one.I saved the data as clt.dta and then I ran the following commands for 100 times and ended up with the following,(I am only using the commands associated with sample of 32,to save space.But I ran the 100 commands for a sample of 2 ,to get the feel of the resulting distribution,) .What I tried to do then was to enter the means of a and b for each run of the commands,but soon enough I discovered that it was an awkward task.I believe that in nc151 there was a part which dealt with zeroing on specific columns to retrieve returned data.Can anyone help me with that,thus saving me from going through all that work of rewriting and then reentering the specific data in edit. Thanks . use clt ,clear . sample 32 (68 observations deleted) . summarize Variable | Obs Mean Std. Dev. Min Max ---------+----------------------------------------------------- a | 32 55.03125 30.70619 5 100 b | 32 18.34375 10.2354 1.666667 33.33333 . . use clt ,clear . sample 32 (68 observations deleted) . summarize Variable | Obs Mean Std. Dev. Min Max ---------+----------------------------------------------------- a | 32 51.34375 30.83736 2 99 b | 32 17.11458 10.27912 .6666667 33 . one hab dATA iAfter generating a triangular distribution ,so as I trtQuoting David Greenberg <dg4@nyu.edu>: > Look for discussions of the Central Limit Theorem. Depending on the > text, you will find formal mathematical demonstrations of the result, or > mathematically undemanding discussions that make the theorem plausible > even if, at first sight, it seems counter-intuitive. David Greenberg > > ----- Original Message ----- > From: kusi@yorku.ca > Date: Sunday, July 21, 2002 3:27 pm > 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/

**Follow-Ups**:**st: RE: Re: entering data***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**References**:**Re: st: Re: normal distributions***From:*David Greenberg <dg4@nyu.edu>

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