
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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