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Anderson-Darling Normality Test

Definition of Anderson-Darling Normality Test:

After you have plotted data for normality test, check for P-value.

P-value < 0.05 = not normal.

Normal = P-value >= 0.05

Note: Similar comparison of P-value is there in Hypothesis Testing.

If P-value > 0.05, fail to reject the H0.

The Anderson-Darling test is used to test if a sample of data came from a population with a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more weight to the tails than does the K-S test. The K-S test is distribution free in the sense that the critical values do not depend on the specific distribution being tested. The Anderson-Darling test makes use of the specific distribution in calculating critical values. This has the advantage of allowing a more sensitive test and the disadvantage that critical values must be calculated for each distribution.

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