Re: [R] Wilcoxon signed rank test and its requirements

From: Frank E Harrell Jr <f.harrell_at_vanderbilt.edu>
Date: Fri, 25 Jun 2010 07:59:37 -0500

The central limit theorem doesn't help. It just addresses type I error, not power.

Frank

On 06/25/2010 04:29 AM, Joris Meys wrote:
> As a remark on your histogram : use less breaks! This histogram tells
> you nothing. An interesting function is ?density , eg :
>
> x<-rnorm(250)
> hist(x,freq=F)
> lines(density(x),col="red")
>
> See also this ppt, a very nice and short introduction to graphics in R :
> http://csg.sph.umich.edu/docs/R/graphics-1.pdf
>
> 2010/6/25 Atte Tenkanen<attenka_at_utu.fi>:

>> Is there anything for me?
>>
>> There is a lot of data, n=2418, but there are also a lot of ties.
>> My sample n250-300

>
> You should think about the central limit theorem. Actually, you can
> just use a t-test to compare means, as with those sample sizes the
> mean is almost certainly normally distributed.
>>
>> i would like to test, whether the mean of the sample differ significantly from the population mean.
>>

> According to probability theory, this will be in 5% of the cases if
> you repeat your sampling infinitly. But as David asked: why on earth
> do you want to test that?
>
> cheers
> Joris
>
-- 
Frank E Harrell Jr   Professor and Chairman        School of Medicine
                     Department of Biostatistics   Vanderbilt University

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Received on Fri 25 Jun 2010 - 13:02:44 GMT

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