Its most common use is for testing whether your data comes from a normal distribution. The Anderson-Darling test is used to test if a sample of data comes from a population with a specific distribution. Overview: What is the Anderson-Darling Normality Test (AD test)? We will also explain the benefits of the AD test and offer a few best practices for understanding when and how to use the AD test. This article will explore what normality of the data means and how the AD test can be used to confirm whether your data will satisfy the assumption of normality. If you fail that assumption, you may need to use a different statistical tool or approach. Many statistical tools you might use have normality as an underlying assumption. Testing for normality is often a first step in analyzing your data. Definition of Anderson-Darling Normality Test: « Back to Glossary Index
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