Ernesto Jardim wrote:
Ok, let me put it the other way around.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:
On another test I have W = 0.9907, p-value = 6.024e-06. The same
question stands, with such huge W should it be expected to be normal ?
EJ
You have it backwards. The null hypothesis is that the distribution is Normal. You reject this null when the p-value is small. If the distribution is Normal, the p-value will tend to be large.______________________________________________
> shapiro.test(rnorm(100))
Shapiro-Wilk normality test
data: rnorm(100)
W = 0.9877, p-value = 0.4894
Rick B.
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> 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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