Re: Determining if samples are normal

[Robert A. Macy]

curious,

why the for loop and not
q1=(1:n)/(n+1);
...?

and why 
[p yf]=polyfit( ...etc...);

when 
p=polyfit(...) is faster?

            - Robert -

On Sun, 25 Sep 2005 14:31:07 -0500
 Doug Stewart <address@hidden> wrote:
> Søren Hauberg wrote:
> 
> > Hi,
> > Does anybody know how I can test wether or not some
> samples are 
> > normaly distributed? I tried graphical methods, such as
> looking at 
> > histograms and qqplots, but I don't trust my own
> judgement enough to 
> > use graphical methods.
> >
> > /Søren
> 
> Here is how I did it:
> You warp it by the normal curve so that 'normal' data
> will produce a streight line.
> Then you check how streight your line is with the cor()
> function..
> A cor=1 is perfect fit.
> A cor =.5 is there is a 50% chance it is from a normal
> distribution. etc.
> The number of data points is also important. etc.
> So if you get cor>.9 you can be happy.
> 
> 
> ## Copyright (C) 2005 doug
> ##
> ## This program is free software; you can redistribute it
> and/or modify
> ## it under the terms of the GNU General Public License
> as published by
> ## the Free Software Foundation; either version 2 of the
> License, or
> ## (at your option) any later version.
> ##
> ## This program is distributed in the hope that it will
> be useful,
> ## but WITHOUT ANY WARRANTY; without even the implied
> warranty of
> ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
>  See the
> ## GNU General Public License for more details.
> ##
> ## You should have received a copy of the GNU General
> Public License
> ## along with this program; if not, write to the Free
> Software
> ## Foundation, Inc., 59 Temple Place, Suite 330, Boston,
> MA 02111-1307 USA
> 
> ## nt(y)
> ## This is a normality test ie. is the data in y a sample
> from a normaly distributed
> ## population?  If this graph is a streight line then it
> is.
> 
> ## Author: Doug Stewart
> ##
> ## 2005-02-10 doug
> ## * Initial revision
> 
> function [ ret ] = nt (y)
> y1=sort(y);
> n=length(y);
> for k=1:n
>     q1(k)=k/(n+1)
> end
> y3=normal_inv(q1);
> 
> ## now find the streight line that fits through the curve
> [p yf]=polyfit(y3,y1',1);
> p
> ##p(2) is the y crossing and is the sample mean
> ##p(1) is the slope and is the  sample standard deveation
>   std
> w3=p(2)+p(1).*y3;
> plot(y3,y1,y3,w3)
> 
> ## now test how good the fit was
> ## it should be greater than   ?     .997
> cor(y1,w3)
> endfunction
> 
> 
> 
> 
> 
> 
>
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