Marta Colombo wrote:
Hi!
Well, if you look at the output:
shapiro.test(rnorm(5000))
    Shapiro-Wilk normality test
data:Â rnorm(5000)
W = 0.9997, p-value = 0.6205
You can see that the p-value is 0.6205 so you can't refuse the normality hypotesis.
H0: normal data   vs H1: not normal
So shapiro.wilk test is saying that your data are normal and it's correct!
Bye
Marta
A large P-value means nothing more than needing more data. No
conclusion is possible. Please read the classic paper Absence of
Evidence is not Evidence for Absence.
Your first sentence is correct, but not the second.
Why test for normality? What downstream method depends on it? If
normality is in doubt why not use a method that doesn't require it?
Frank Harrell
----- Messaggio originale -----
Da: C.H. <[EMAIL PROTECTED]>
A: "Bunny, lautloscrew.com" <[EMAIL PROTECTED]>
Cc: r-help@r-project.org
Inviato: Domenica 13 luglio 2008, 7:27:43
Oggetto: Re: [R] shapiro wilk normality test
You may consider the nortest package.
http://cran.r-project.org/web/packages/nortest/index.html
Regards,
CH
On Sat, Jul 12, 2008 at 11:30 PM, Bunny, lautloscrew.com
<[EMAIL PROTECTED]> wrote:
Hi everybody,
somehow i dont get the shapiro wilk test for normality. i just can´t find
what the H0 is .
i tried :
 shapiro.test(rnorm(5000))
    Shapiro-Wilk normality test
data:Â rnorm(5000)
W = 0.9997, p-value = 0.6205
If normality is the H0, the test says it´s probably not normal, doesn´t it ?
5000 is the biggest n allowed by the test...
are there any other test ? ( i know qqnorm already ;)
thanks in advance
matthias
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------------------------------------------------------------------------
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--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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