Ernesto Jardim wrote:
HiFirst, the convention is to place replies at the bottom of the last message. (I would prefer it otherwise, but that is the convention.)
It's a bootstrap empirical distribution and has 1000 replicates.
EJ
On Mon, 2003-02-10 at 15:33, Richard A. Bilonick wrote:
It depends on how non-Normal the distribution and the size of the sample. A t-distribution with df = 30 isn't Normal but it is close to being Normal. A small sample size probably won't detect it:
> shapiro.test(rt(100,30))
Shapiro-Wilk normality test
data: rt(100, 30)
W = 0.9927, p-value = 0.8708
But a large enough sample size will:
> shapiro.test(rt(2000,30))
Shapiro-Wilk normality test
data: rt(2000, 30)
W = 0.9968, p-value = 0.0003097
You haven't told us your sample size.
Rick B.
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Apparently even with your "large" sample size, it is not large enough to differentiate a difference between your distribution and the Normal. The difference can't be distinguished from a chance departure from the Normal for the given sample size. There is nothing unusual in this that I can see. It just tends to take huge sample sizes to pick up small differences (assuming your distribution actually differs from the Normal!).
Rick B.
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