From: Atte Tenkanen <attenka_at_utu.fi>

Date: Fri, 25 Jun 2010 08:04:23 +0300

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Fri 25 Jun 2010 - 07:07:11 GMT

Date: Fri, 25 Jun 2010 08:04:23 +0300

The values come from this kind of process: The musical composition is segmented into so-called 'pitch-class segments' and these segments are compared with one reference set with a distance function. Only some distance values are possible. These distance values can be averaged over music bars which produces smoother distribution and the 'comparison curve' that illustrates the distances according to the reference set through a musical piece result in more readable curve (see e.g. http://users.utu.fi/attenka/with6.jpg ), but I would prefer to use original values.

then, I want to pick only some regions from the piece and compare those values of those regions, whether they are higher than the mean of all values.

Atte

> On Jun 24, 2010, at 6:58 PM, Atte Tenkanen wrote:

*>
**> > Is there anything for me?
**> >
**> > There is a lot of data, n=2418, but there are also a lot of ties.
**> > My sample n¡Ö250-300
**> >
**>
**> I do not understand why there should be so many ties. You have not
**> described the measurement process or units. ( ... although you offer a
**>
**> glipmse without much background later.)
**>
**> > i would like to test, whether the mean of the sample differ
**> > significantly from the population mean.
**>
**> Why? What is the purpose of this investigation? Why should the mean of
**>
**> a sample be that important?
**>
**> >
**> > The histogram of the population looks like in attached histogram,
**> > what test should I use? No choices?
**> >
**> > This distribution comes from a musical piece and the values are
**> > 'tonal distances'.
**> >
**> > http://users.utu.fi/attenka/Hist.png
**>
**> That picture does not offer much insidght into the features of that
**> measurement. It appears to have much more structure than I would
**> expect for a sample from a smooth unimodal underlying population.
**>
**> --
**> David.
**>
**> >
**> > Atte
**> >
**> >> On 06/24/2010 12:40 PM, David Winsemius wrote:
**> >>>
**> >>> On Jun 23, 2010, at 9:58 PM, Atte Tenkanen wrote:
**> >>>
**> >>>> Thanks. What I have had to ask is that
**> >>>>
**> >>>> how do you test that the data is symmetric enough?
**> >>>> If it is not, is it ok to use some data transformation?
**> >>>>
**> >>>> when it is said:
**> >>>>
**> >>>> "The Wilcoxon signed rank test does not assume that the data are
**> >>>> sampled from a Gaussian distribution. However it does assume that
**>
**> >>>> the
**> >>>> data are distributed symmetrically around the median. If the
**> >>>> distribution is asymmetrical, the P value will not tell you much
**>
**> >>>> about
**> >>>> whether the median is different than the hypothetical value."
**> >>>
**> >>> You are being misled. Simply finding a statement on a statistics
**> >>> software website, even one as reputable as Graphpad (???), does not
**> >> mean
**> >>> that it is necessarily true. My understanding (confirmed reviewing
**> >>> "Nonparametric statistical methods for complete and censored data"
**> >> by M.
**> >>> M. Desu, Damaraju Raghavarao, is that the Wilcoxon signed-rank test
**> >> does
**> >>> not require that the underlying distributions be symmetric. The
**> >>> above
**> >>> quotation is highly inaccurate.
**> >>>
**> >>
**> >> To add to what David and others have said, look at the kernel that
**>
**> >> the
**> >>
**> >> U-statistic associated with the WSR test uses: the indicator (0/1)
**> of
**> >> xi
**> >> + xj > 0. So WSR tests H0:p=0.5 where p = the probability that the
**> >> average of a randomly chosen pair of values is positive. [If there
**> >> are
**> >> ties this probably needs to be worded as P[xi + xj > 0] = P[xi + xj
**> <
**> >>
**> >> 0], i neq j.
**> >>
**> >> Frank
**> >>
**> >> --
**> >> Frank E Harrell Jr Professor and Chairman School of Medicine
**> >> Department of Biostatistics Vanderbilt
**> >> University
*

>

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