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Date:         Tue, 4 Oct 2005 09:26:24 -0400
Reply-To:     Venita DePuy <depuy001@NOTES.DUKE.EDU>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Venita DePuy <depuy001@NOTES.DUKE.EDU>
Subject:      Re: draw a normal distribution (also lognormal)
Comments: To: Jianping Zhu <zhujp98@gmail.com>
In-Reply-To:  <6716d5d0510032132k10b07edau40c3175d509243a7@mail.gmail.com>
Content-Type: text/plain; charset="US-ASCII"

You can also use the method Rene mentioned, in Proc Univariate instead of Proc Capability. -Venita

data file1; do i = 1 to 100; j = rannor(i); k = exp(j); output; end;

run; symbol v=circle cv=blue; *to test distribution; proc univariate data=file1; var j k; histogram; QQPLOT / normal (mu=est sigma=est); run;

Thanks. one more question, how can i use QQ plot to check the mormality of generated sample in this case? Thanks again.

On 10/4/05, Venita DePuy <depuy001@notes.duke.edu> wrote: > > I believe the following will create a normal distribution (with mean 0 and > std dev 1) Note that it looks much more normal if you use 1000 points, > etc. > If you want to get particular, you can have Proc Univariate draw in lines > for what a normal and/or lognormal distribution, with the mean/std dev of > the data, should look like. > > > Hope this helps. > j is normally distributed. > k is lognormally distributed. > > You can do a simple transformation for a lognormal distribution. > >


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