non-parametric methods

Non-parametric methods are statistical techniques that do not assume a specific mathematical form for the underlying data distribution. Instead of using fixed parameters (like the mean or standard deviation) to model data, they analyze data directly, making fewer assumptions. This flexibility allows non-parametric methods to be effective when data doesn’t fit common distribution patterns or when the sample size is small. They are often used for tasks like comparing groups or estimating relationships without relying on predefined models, making them versatile tools for analyzing complex or unusual data structures in a reliable way.