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I get two lines, which one I use and how can I interpret it then? I mean how can I say that the distribution is more or less similar to student with 8 degrees?



Houda GUESSAB



-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: mardi 21 août 2012 11:27
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: ksmirnov

When you say the qnormal function, I presume you mean the -qnorm- command.

There is no one way to do it. With the normal distribution, most
people regard matching means and SDs to be the way to do it, but there
is a good case for fitting a more robust line. In the case of t with 8
d.f. (henceforth t(8))  the case is even stronger. By my calculation
t(8) has SD = sqrt(8/6) = sqrt(4/3), but you could use the IQR or any
other pair of quantiles. Similarly, although t(8) has mean, median and
any other measure of level all 0, it is open for discussion how the
data should be summarized. It may even be that 0 is a natural
reference for whatever your data are.

The straight lines come from manipulating

(observed y - level for y) / (expected x - level for x) = (spread for
y) / (spread for x)

where in practice level for x is always 0.

Example code:

 sysuse auto, clear
 egen rank = rank(mpg), unique
 su rank, meanonly
 gen expected = -invttail(8, (rank - 0.5) / `r(max)')
 su mpg, detail
 local mean = r(mean)
 local sd = r(sd)
 local median = r(p50)
 local iqr = r(p75) - r(p25)


 scatter mpg expected ///
|| function t_8 = `mean' + x * `sd' / sqrt(4/3), ra(exp) ///
|| function t_8_2 = `median' + x * `iqr' / (2 * invttail(8, 0.25)), ra(exp)


On Tue, Aug 21, 2012 at 9:41 AM, Guessab Houda
<houda.guessab@gre.generali.com> wrote:
> OK you are right. Then I will use the program you sent me.
>
> sysuse auto, clear
>>> egen rank = rank(mpg), unique
>>> su mpg, meanonly
>>> local N = r(N)
>>> gen tquantile = -invttail(8, (rank - 0.5) / `N')
>>> scatter mpg tquantile
>
> I just need to draw 45 degree reference line like the qnormal function does; can you help me with that?
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