Epidemiological data often violate the assumptions of parametric tests, such as normality and homogeneity of variances. Non-parametric methods are robust and flexible, making them suitable for a variety of data types and research questions. They are particularly useful for analyzing survival data, categorical data, and ordinal scales. Additionally, non-parametric methods can be applied to small sample sizes, which are common in epidemiological studies.
