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
[email protected]
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
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