Anderson-Darling Test


The Anderson-Darling test is a statistical test that measures whether a given data sample is drawn from a specific probability distribution. It is a modification of the Kolmogorov-Smirnov test and gives more weight to the tails than the middle of the distribution. The test calculates a test statistic that compares the empirical distribution function of the sample with the cumulative distribution function of the theoretical distribution. The test statistic is compared with critical values from the Anderson-Darling distribution to determine whether to reject the null hypothesis that the sample comes from the specified distribution. The test is commonly used in data science to test the goodness of fit of a model or to compare two different models.


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