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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: testing normalitt of data |

Date |
Mon, 29 Jun 2009 16:22:39 +0100 |

I don't understand all of this (what are all the standard error results?) but I have comments nevertheless: 1. Although normality is a formal requirement for the t test there is a widespread view that it is not always very crucial. For more discussion, see for example Rupert G. Miller. 1986. Beyond ANOVA. New York: Wiley. 2. You cite here results for one set of data, but the whole point of a t test is that you are comparing two groups. 3. It is not very safe to base judgments of (non-)normality solely on measures of skewness and kurtosis. Plot the data too if you are not doing so already. 4. Perhaps the easiest extra thing you can do is add a parallel Mann-Whitney test and see how far the P-value matches that from a t-test. 5. The research problem is not stated here, but a -qqplot- or -dotplot- is often more informative about a comparison of groups than a bare t-test. Nick n.j.cox@durham.ac.uk El Hawary can I use the t-test for independent samples when the skewness and kurtosis of data are as follow skewness: -1.232 & the std. error of skewness is .616/ .044 and the std. error of skewness is .427 kurtosis: 2.195 & the std. error of kurtosis is 1.191/ -.505 and the std. error of kurtosis is .833 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: testing normalitt of data***From:*El Hawary <elhawary99@yahoo.com>

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