Hello,
While doing test of normality under R and SAS, in order to prove the efficiency
of R to my company, I notice
that Anderson Darling, Cramer Van Mises and Shapiro-Wilk tests results are
quite the same under the two environnements,
but the Kolmogorov-smirnov p-value really is different.
Here is what I do:
> ks.test(w,pnorm,mean(w),sd(w))
One-sample Kolmogorov-Smirnov test
data: w
D = 0.2143, p-value = 0.3803
alternative hypothesis: two.sided
> w
[1] 3837 3334 2208 1745 2576 3208 3746 3523 3430 3480 3116 3428 2184 2383 3500
3866 3542
[18] 3278
SAS results:
Kolmogorov-Smirnov D 0.214278 Pr > D 0.0271
Why is the p-value so high under R? Much higher than with other tests.
Best regards,
Anthony Landrevie (French Student)
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