Nonparametric tests

Nonparametric tests are statistical methods used to analyze data without assuming it follows a specific distribution, like the normal curve. They are useful when data is skewed, has outliers, or when the sample size is small. Instead of relying on parameters (like averages or variances), these tests focus on the data’s ordinal or ranked information. This makes them flexible and robust for various types of data, allowing researchers to compare groups or assess relationships without the strict assumptions required by traditional parametric tests.