Summary
Nonparametric methods provide flexible and robust alternatives to parametric tests, especially when the assumption of normality is violated or when data are inherently ordinal or categorical. Key tools include the sign test, Wilcoxon signed?rank test for paired data, and the Wilcoxon rank?sum test for independent samples, with permutation tests serving as exact methods for small or tied data. Understanding when to apply these methods—based on data type and study design—is crucial for valid statistical inference in fields such as medicine, biology, and social sciences.