Course 14 Nonparametric Method

Non-parametric methods are statistical techniques that do not assume a specific parametric form for the underlying data distribution. Unlike parametric methods, which rely on predefined models (such as normality), non-parametric methods offer flexibility by focusing on the ranks, orders, or counts of data rather than their exact values. These methods are particularly useful when the data is ordinal or skewed or when assumptions about the population distribution cannot be verified. Non-parametric methods provide powerful tools for hypothesis testing, estimation, and regression, making them essential when classical parametric assumptions are difficult to meet or not applicable.