In article <nH9u6.6370$[EMAIL PROTECTED]>,
W. D. Allen Sr. <[EMAIL PROTECTED]> wrote:
>A common mistake made in statistical inference is to assume every data set
>is normally distributed. This seems to be the rule rather than the
>exception, even among professional statisticians.
NOTHING is normally distributed. However, many of the
procedures are not overly sensitive to normality. One
should know which are and which are not.
>Either the Chi Square or S-K test, as appropriate, should be conducted to
>determine normality before interpreting population percentages using
>standard deviations.
The chi squared test has very little power; not rejecting
the null hypothesis is not a guarantee that it is even a
fair fit.
Interpreting percentages as standard deviations is essentially
a meaningless procedure in any case.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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