The Anderson-Darling Test

In many cases, the distribution of the population from where the random samples are drawn is often unknown or difficult to determine.

In these cases, the Anderson-Darling test can aid in determining if such data and samples are drawn from a particular distribution, such as standard normal or uniform distribution.

When testing for normality, the null hypothesis states that the data follow a normal distribution, and the alternative hypothesis is that the data do not follow a normal distribution.

The test statistic A² is calculated using the following equation to test for the normality of samples and compared with the critical value obtained from the theoretical standard normal distribution.

When this test statistic is greater than the critical value at a pre-decided significance level, the null hypothesis that the sample is from a normal distribution is rejected.

The data from laboratory experiments or even from natural observations are often assumed to be normally distributed.

The Anderson-Darling test can be applied to decide the appropriate parametric or nonparametric test for the analysis.