03-25-2012 11:05 PM
Dear All,
Thanks for explain the follwoing table for me,whether this field check for normality with the answer to its normal distribution yes/no?
thanks.
Further, what if the three tests have contradiction?
Tests for Normality | ||||
Test | Statictice | P Value | ||
Kolmogorov-Smirnov | D | 0.064727 | Pr > D | >0.15 |
Cramer-von Mises | W-Sq | 0.21097 | Pr > W-Sq | 0.2014 |
Anderson-Darling | A-Sq | 1.28515 | Pr > A-Sq | 0.1916 |
03-26-2012 04:12 AM
From your P value. Should refuse H0 : distribution is Normal , if alpha is 0.05 .
W is usually used when size of sample is small.
A is ususally used when size of sample is large.
I recommend to use A.
Maybe some expert can give you a whole explaination.
Ksharp
03-26-2012 04:12 AM
From your P value. Should refuse H0 : distribution is Normal , if alpha is 0.05 .
W is usually used when size of sample is small.
A is ususally used when size of sample is large.
I recommend to use A.
Maybe some expert can give you a whole explaination.
Ksharp
03-26-2012 04:17 AM
Ksharp, Thank you very much.
03-26-2012 11:16 AM
bbb_NG, the way to interpret the results you posted is that about one out of five (20%) samples of the size you analysed would have a distribution that looks further away from the normal than yours, just by chance. As Ksharp mentioned, we usually reject the hypothesis of normality when there is little chance, less than one in 20, that our sample could arise from the sampling of a normal population. Thus, we must conclude that the hypothesis of normality cannot be rejected for your data.
The tests do not contradict each other. They simply look at different aspects of the data distribution and compare it to what is expected from the normal distribution. By analogy, one could say that an animal is a bird because it has feathers and no teeth while someone else would require that it flies and lays eggs. They look at different aspects.
Hope this helps.
PG
03-26-2012 09:11 PM
PG,Thanks, it do helps.
01-16-2013 09:24 AM
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