The Anderson-Darling Test is a statistical test used to determine if a sample of data comes from a specific distribution, typically the normal distribution. It assesses how well the data fits the chosen distribution by comparing the empirical distribution function of the sample to the expected distribution. A smaller test statistic indicates a better fit. This test is particularly useful because it gives more weight to the tails of the distribution, making it sensitive to deviations in those areas. It is commonly applied in fields like quality control and finance to validate assumptions about data distributions before further analysis.